diff --git a/.gitattributes b/.gitattributes
index a6344aac8c09253b3b630fb776ae94478aa0275b..43c3861ee69c575e8d96e4c4cc676473746000b6 100644
--- a/.gitattributes
+++ b/.gitattributes
@@ -33,3 +33,14 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+checkpoint-1025/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+checkpoint-1230/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+checkpoint-1435/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+checkpoint-1640/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+checkpoint-1842/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+checkpoint-205/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+checkpoint-410/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+checkpoint-615/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+checkpoint-820/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+final/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text
diff --git a/.ipynb_checkpoints/plot_loss_from_trainer_state-checkpoint.py b/.ipynb_checkpoints/plot_loss_from_trainer_state-checkpoint.py
new file mode 100644
index 0000000000000000000000000000000000000000..eaf442644d02d8625f8186aa6d050495712cd2f9
--- /dev/null
+++ b/.ipynb_checkpoints/plot_loss_from_trainer_state-checkpoint.py
@@ -0,0 +1,160 @@
+# -*- coding: utf-8 -*-
+"""
+Usage:
+  python plot_loss_from_trainer_state.py --input trainer_state.json --outdir ./plots \
+         --checkpoint_steps 263,526,789,1052
+
+功能:
+- Curve: 黃橘色實線
+- Grid: x,y 虛線
+- Epoch markers: 藍色虛線 + EpochN 標籤（含最後一個 epoch）
+- Checkpoints: 藍色小圓點（線性插值；超出範圍時使用端點值，並自動擴張 x 軸確保能看見）
+"""
+import json, argparse
+from pathlib import Path
+import matplotlib.pyplot as plt
+import numpy as np
+
+YELLOW_ORANGE = "#d58f00"
+BLUE = "#1f77b4"
+
+def find_epoch_boundaries(log_items):
+    """找到每個 epoch 邊界 (包含最後一個)"""
+    boundaries = []
+    prev_epoch_int = None
+    seen = set()
+    last_step, last_epoch = None, None
+    for it in log_items:
+        step = it.get("step")
+        ep = it.get("epoch")
+        if step is None or ep is None:
+            continue
+        last_step, last_epoch = step, ep
+        ep_int = int(ep)
+        if prev_epoch_int is None:
+            prev_epoch_int = ep_int
+            continue
+        if ep_int != prev_epoch_int:
+            if (step, ep_int) not in seen and ep_int >= 1:
+                boundaries.append((step, ep_int))
+                seen.add((step, ep_int))
+            prev_epoch_int = ep_int
+    # 最後一個 epoch 也補上
+    if last_step is not None and last_epoch is not None:
+        ep_final = int(float(last_epoch)) + 1
+        if (last_step, ep_final) not in seen:
+            boundaries.append((last_step, ep_final))
+    boundaries.sort(key=lambda x: x[0])
+    return boundaries
+
+def plot_series(x, y, xlabel, ylabel, title, outpath,
+                epoch_marks=None, checkpoint_steps=None,
+                color=YELLOW_ORANGE, linestyle='-'):
+    fig = plt.figure(figsize=(10,6))
+    ax = fig.add_subplot(111)
+    ax.plot(x, y, color=color, linestyle=linestyle, linewidth=2)
+
+    # 標記 checkpoint 藍點（線性插值；邊界外使用端點值）
+    extra_x = []
+    if checkpoint_steps:
+        for s in checkpoint_steps:
+            y_interp = np.interp(s, x, y, left=y[0], right=y[-1])
+            ax.plot(s, y_interp, marker='o', color=BLUE, markersize=6)
+            extra_x.append(s)
+
+    # === 計算 x 範圍時把 epoch 標線也納入，並加右側 padding ===
+    xmin = 0
+    all_x_candidates = [max(x)]
+    if extra_x:
+        all_x_candidates.append(max(extra_x))
+    if epoch_marks:
+        # 把所有 epoch 標線的 step 納入考量
+        ep_steps = [s for (s, _) in epoch_marks]
+        if ep_steps:
+            all_x_candidates.append(max(ep_steps))
+
+    xmax_base = max(all_x_candidates) if all_x_candidates else x[-1]
+
+    # 右邊加一點 margin，避免剛好貼齊看不到線
+    span = max(xmax_base - xmin, 1.0)
+    right_pad = max(1.0, 0.02 * span)   # 至少 +1 step 或 2% 寬度
+    ax.set_xlim(left=xmin, right=xmax_base + right_pad)
+
+    # y 仍從 0 起
+    ax.set_ylim(bottom=0)
+
+    # 虛線格線
+    ax.grid(True, which='major', axis='both', linestyle='--', linewidth=0.8, alpha=0.6)
+
+    # epoch 標記 (藍色虛線)
+    if epoch_marks:
+        for step, ep in epoch_marks:
+            ax.axvline(x=step, color=BLUE, linestyle='--', linewidth=1.2)
+            ymax = ax.get_ylim()[1]
+            ax.text(step, ymax*0.98, f'Epoch{ep}', rotation=90,
+                    va='top', ha='right', fontsize=8, color=BLUE)
+
+    # label & look（放到最後避免被 set_xlim/set_ylim 影響）
+    ax.set_xlabel(xlabel); ax.set_ylabel(ylabel); ax.set_title(title)
+    ax.spines['left'].set_linewidth(2); ax.spines['bottom'].set_linewidth(2)
+    ax.spines['right'].set_visible(False); ax.spines['top'].set_visible(False)
+
+    fig.savefig(outpath, bbox_inches="tight")
+    plt.close(fig)
+
+
+def main():
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--input", required=True, help="Path to trainer_state.json")
+    ap.add_argument("--outdir", default="./plots", help="Directory to save PNGs")
+    ap.add_argument("--no_epoch_marks", action="store_true", help="Disable vertical epoch markers")
+    ap.add_argument("--checkpoint_steps", default="", help="Comma-separated steps (e.g., 100,200,500)")
+    args = ap.parse_args()
+
+    src = Path(args.input)
+    with open(src, "r", encoding="utf-8") as f:
+        state = json.load(f)
+
+    log = state.get("log_history", state.get("logs", []))
+
+    steps, train_losses = [], []
+    eval_steps, eval_losses = [], []
+    lr_steps, lrs = [], []
+
+    for item in log:
+        step = item.get("step")
+        if step is None: 
+            continue
+        if "loss" in item:
+            steps.append(step); train_losses.append(item["loss"])
+        if "eval_loss" in item:
+            eval_steps.append(step); eval_losses.append(item["eval_loss"])
+        if "learning_rate" in item:
+            lr_steps.append(step); lrs.append(item["learning_rate"])
+
+    outdir = Path(args.outdir); outdir.mkdir(parents=True, exist_ok=True)
+
+    epoch_marks = None if args.no_epoch_marks else find_epoch_boundaries(log)
+    # 允許空白與混合格式
+    raw = [s.strip() for s in args.checkpoint_steps.replace("，", ",").split(",") if s.strip()]
+    checkpoint_steps = []
+    for s in raw:
+        try:
+            checkpoint_steps.append(int(float(s)))
+        except:
+            pass
+
+    if steps and train_losses:
+        plot_series(steps, train_losses, "Step", "Training Loss", "Training Loss vs Step",
+                    outdir / "loss_curve.png", epoch_marks=epoch_marks, checkpoint_steps=checkpoint_steps)
+    if eval_steps and eval_losses:
+        plot_series(eval_steps, eval_losses, "Step", "Eval Loss", "Eval Loss vs Step",
+                    outdir / "eval_loss_curve.png", epoch_marks=epoch_marks, checkpoint_steps=checkpoint_steps)
+    if lr_steps and lrs:
+        plot_series(lr_steps, lrs, "Step", "Learning Rate", "Learning Rate vs Step",
+                    outdir / "lr_curve.png", epoch_marks=epoch_marks, checkpoint_steps=checkpoint_steps)
+
+    print(f"Saved plots to: {outdir.resolve()}")
+
+if __name__ == "__main__":
+    main()
diff --git a/README.md b/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..20c165c7feaa880a18e0662941a5b246a698be2e
--- /dev/null
+++ b/README.md
@@ -0,0 +1,209 @@
+---
+base_model: Salesforce/Llama-xLAM-2-8b-fc-r
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:Salesforce/Llama-xLAM-2-8b-fc-r
+- lora
+- sft
+- transformers
+- trl
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.17.1
\ No newline at end of file
diff --git a/adapter_config.json b/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..9eda25bff7c128105e91aa1a00507aaa31dd53fd
--- /dev/null
+++ b/adapter_config.json
@@ -0,0 +1,39 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "Salesforce/Llama-xLAM-2-8b-fc-r",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "v_proj",
+    "k_proj",
+    "o_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/adapter_model.safetensors b/adapter_model.safetensors
new file mode 100644
index 0000000000000000000000000000000000000000..850b8a7b7e98c250c049c275821793dc06f6bd0f
--- /dev/null
+++ b/adapter_model.safetensors
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9dfa231e6a429050ed62c5c2fd8478b22f783cde633e267292cba7c756066ef2
+size 54560368
diff --git a/checkpoint-1025/README.md b/checkpoint-1025/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..20c165c7feaa880a18e0662941a5b246a698be2e
--- /dev/null
+++ b/checkpoint-1025/README.md
@@ -0,0 +1,209 @@
+---
+base_model: Salesforce/Llama-xLAM-2-8b-fc-r
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:Salesforce/Llama-xLAM-2-8b-fc-r
+- lora
+- sft
+- transformers
+- trl
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.17.1
\ No newline at end of file
diff --git a/checkpoint-1025/adapter_config.json b/checkpoint-1025/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..9eda25bff7c128105e91aa1a00507aaa31dd53fd
--- /dev/null
+++ b/checkpoint-1025/adapter_config.json
@@ -0,0 +1,39 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "Salesforce/Llama-xLAM-2-8b-fc-r",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "v_proj",
+    "k_proj",
+    "o_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}
\ No newline at end of file
diff --git a/checkpoint-1025/adapter_model.safetensors b/checkpoint-1025/adapter_model.safetensors
new file mode 100644
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+  },
+  "additional_special_tokens": [
+    "<|eot_id|>",
+    "<|eom_id|>"
+  ],
+  "bos_token": "<|begin_of_text|>",
+  "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n    {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n    {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not tools is defined %}\n    {%- set tools = none %}\n{%- endif %}\n\n{#- Extract system message #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if messages[0]['role'] == 'system' %}\n    {%- set system_message = messages[0]['content'] | trim %}\n    {%- set messages = messages[1:] %}\n    {{- system_message + \"\\n\" }}\n{%- else %}\n    {%- set system_message = \"You are a helpful assistant that can use tools. You are developed by Salesforce xLAM team.\" %}\n    {% set format_instruction %}You have access to a set of tools. When using tools, make calls in a single JSON array: \n\n[{\"name\": \"tool_call_name\", \"arguments\": {\"arg1\": \"value1\", \"arg2\": \"value2\"}}, ... (additional parallel tool calls as needed)]\n\nIf no tool is suitable, state that explicitly. If the user's input lacks required parameters, ask for clarification. Do not interpret or respond until tool results are returned. Once they are available, process them or make additional calls if needed. For tasks that don't require tools, such as casual conversation or general advice, respond directly in plain text. The available tools are:{% endset %}\n    {{- system_message + \"\\n\" }}\n    {%- if tools is not none %}\n        {{- format_instruction + \"\\n\\n\" }}\n    {%- endif %}\n{%- endif %}\n\n\n{%- if tools is not none %}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\\n\\n\" }}\n    {%- endfor %}\n{%- endif %}\n{{- \"<|eot_id|>\" }}\n\n{%- for message in messages %}\n    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n    {%- elif 'tool_calls' in message %}\n        {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n        {%- if message['tool_calls'] %}\n            {{- \"[\" }}\n            {%- for tool_call_function in message.tool_calls %}\n                {%- set tool_call = tool_call_function.function %}\n                {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n                {{- '\"arguments\": ' }}\n                {{- tool_call.arguments | tojson }}\n                {{- \"}\" }}\n                {%- if not loop.last %}\n                    {{- \", \" }}\n                {%- endif %}\n            {%- endfor %}\n            {{- \"]\" }}\n            {{- \"<|eot_id|>\" }}\n        {%- elif message['content'] %}\n            {{- message['content'] | trim + '<|eot_id|>' }}\n        {%- else %}\n            {{- \"[]\\n\" + '<|eot_id|>' }}\n        {%- endif %}\n    {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n        {{- \"<|start_header_id|>\" + \"ipython\" + \"<|end_header_id|>\\n\\n\" }}\n        {%- set content = message[\"content\"] %}\n        {%- if content is mapping or (content is iterable and content is not string) %}\n            {{- content | tojson }}\n        {%- else %}\n            {{- content }}\n        {%- endif %}\n        {{- \"<|eot_id|>\" }}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}",
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|eot_id|>",
+  "extra_special_tokens": {},
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 16384,
+  "pad_token": "<|eot_id|>",
+  "padding_side": "right",
+  "split_special_tokens": false,
+  "tokenizer_class": "PreTrainedTokenizerFast"
+}
diff --git a/checkpoint-1025/trainer_state.json b/checkpoint-1025/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..8d2cef3b8ba9d16091fe51adf71728423217c071
--- /dev/null
+++ b/checkpoint-1025/trainer_state.json
@@ -0,0 +1,787 @@
+{
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+  "best_model_checkpoint": "./xlam_lora_new_ete_over_size_3epoch_multi_mix/checkpoint-1025",
+  "epoch": 1.6686167777382104,
+  "eval_steps": 205,
+  "global_step": 1025,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
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diff --git a/checkpoint-1230/README.md b/checkpoint-1230/README.md
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+---
+base_model: Salesforce/Llama-xLAM-2-8b-fc-r
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:Salesforce/Llama-xLAM-2-8b-fc-r
+- lora
+- sft
+- transformers
+- trl
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.17.1
\ No newline at end of file
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\ No newline at end of file
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+  "additional_special_tokens": [
+    "<|eot_id|>",
+    "<|eom_id|>"
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+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|eot_id|>",
+  "extra_special_tokens": {},
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
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+  "model_max_length": 16384,
+  "pad_token": "<|eot_id|>",
+  "padding_side": "right",
+  "split_special_tokens": false,
+  "tokenizer_class": "PreTrainedTokenizerFast"
+}
diff --git a/checkpoint-1230/trainer_state.json b/checkpoint-1230/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..1f2b0b3f4aaf79727c6e007c949c235378a43e93
--- /dev/null
+++ b/checkpoint-1230/trainer_state.json
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diff --git a/checkpoint-1435/README.md b/checkpoint-1435/README.md
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+---
+base_model: Salesforce/Llama-xLAM-2-8b-fc-r
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:Salesforce/Llama-xLAM-2-8b-fc-r
+- lora
+- sft
+- transformers
+- trl
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.17.1
\ No newline at end of file
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\ No newline at end of file
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+    "<|eot_id|>",
+    "<|eom_id|>"
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+version https://git-lfs.github.com/spec/v1
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diff --git a/checkpoint-1640/README.md b/checkpoint-1640/README.md
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+---
+base_model: Salesforce/Llama-xLAM-2-8b-fc-r
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:Salesforce/Llama-xLAM-2-8b-fc-r
+- lora
+- sft
+- transformers
+- trl
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.17.1
\ No newline at end of file
diff --git a/checkpoint-1640/adapter_config.json b/checkpoint-1640/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..9eda25bff7c128105e91aa1a00507aaa31dd53fd
--- /dev/null
+++ b/checkpoint-1640/adapter_config.json
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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "Salesforce/Llama-xLAM-2-8b-fc-r",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
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+  },
+  "additional_special_tokens": [
+    "<|eot_id|>",
+    "<|eom_id|>"
+  ],
+  "bos_token": "<|begin_of_text|>",
+  "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n    {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n    {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not tools is defined %}\n    {%- set tools = none %}\n{%- endif %}\n\n{#- Extract system message #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if messages[0]['role'] == 'system' %}\n    {%- set system_message = messages[0]['content'] | trim %}\n    {%- set messages = messages[1:] %}\n    {{- system_message + \"\\n\" }}\n{%- else %}\n    {%- set system_message = \"You are a helpful assistant that can use tools. You are developed by Salesforce xLAM team.\" %}\n    {% set format_instruction %}You have access to a set of tools. When using tools, make calls in a single JSON array: \n\n[{\"name\": \"tool_call_name\", \"arguments\": {\"arg1\": \"value1\", \"arg2\": \"value2\"}}, ... (additional parallel tool calls as needed)]\n\nIf no tool is suitable, state that explicitly. If the user's input lacks required parameters, ask for clarification. Do not interpret or respond until tool results are returned. Once they are available, process them or make additional calls if needed. For tasks that don't require tools, such as casual conversation or general advice, respond directly in plain text. The available tools are:{% endset %}\n    {{- system_message + \"\\n\" }}\n    {%- if tools is not none %}\n        {{- format_instruction + \"\\n\\n\" }}\n    {%- endif %}\n{%- endif %}\n\n\n{%- if tools is not none %}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\\n\\n\" }}\n    {%- endfor %}\n{%- endif %}\n{{- \"<|eot_id|>\" }}\n\n{%- for message in messages %}\n    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n    {%- elif 'tool_calls' in message %}\n        {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n        {%- if message['tool_calls'] %}\n            {{- \"[\" }}\n            {%- for tool_call_function in message.tool_calls %}\n                {%- set tool_call = tool_call_function.function %}\n                {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n                {{- '\"arguments\": ' }}\n                {{- tool_call.arguments | tojson }}\n                {{- \"}\" }}\n                {%- if not loop.last %}\n                    {{- \", \" }}\n                {%- endif %}\n            {%- endfor %}\n            {{- \"]\" }}\n            {{- \"<|eot_id|>\" }}\n        {%- elif message['content'] %}\n            {{- message['content'] | trim + '<|eot_id|>' }}\n        {%- else %}\n            {{- \"[]\\n\" + '<|eot_id|>' }}\n        {%- endif %}\n    {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n        {{- \"<|start_header_id|>\" + \"ipython\" + \"<|end_header_id|>\\n\\n\" }}\n        {%- set content = message[\"content\"] %}\n        {%- if content is mapping or (content is iterable and content is not string) %}\n            {{- content | tojson }}\n        {%- else %}\n            {{- content }}\n        {%- endif %}\n        {{- \"<|eot_id|>\" }}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}",
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|eot_id|>",
+  "extra_special_tokens": {},
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 16384,
+  "pad_token": "<|eot_id|>",
+  "padding_side": "right",
+  "split_special_tokens": false,
+  "tokenizer_class": "PreTrainedTokenizerFast"
+}
diff --git a/checkpoint-1640/trainer_state.json b/checkpoint-1640/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..ea6992b1dea59881e3058cc0fd0cbcd5c04e6a45
--- /dev/null
+++ b/checkpoint-1640/trainer_state.json
@@ -0,0 +1,1245 @@
+{
+  "best_metric": 0.21331782639026642,
+  "best_model_checkpoint": "./xlam_lora_new_ete_over_size_3epoch_multi_mix/checkpoint-1640",
+  "epoch": 2.6697868443811363,
+  "eval_steps": 205,
+  "global_step": 1640,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
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+      "grad_norm": 0.7572630643844604,
+      "learning_rate": 2.688172043010753e-06,
+      "loss": 0.5223,
+      "step": 10
+    },
+    {
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+      "learning_rate": 5.376344086021506e-06,
+      "loss": 0.4858,
+      "step": 20
+    },
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+      "learning_rate": 8.064516129032258e-06,
+      "loss": 0.4246,
+      "step": 30
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+    {
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+      "grad_norm": 0.2949349582195282,
+      "learning_rate": 1.0752688172043012e-05,
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diff --git a/checkpoint-1842/README.md b/checkpoint-1842/README.md
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+---
+base_model: Salesforce/Llama-xLAM-2-8b-fc-r
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:Salesforce/Llama-xLAM-2-8b-fc-r
+- lora
+- sft
+- transformers
+- trl
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.17.1
\ No newline at end of file
diff --git a/checkpoint-1842/adapter_config.json b/checkpoint-1842/adapter_config.json
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\ No newline at end of file
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+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|eot_id|>",
+  "extra_special_tokens": {},
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 16384,
+  "pad_token": "<|eot_id|>",
+  "padding_side": "right",
+  "split_special_tokens": false,
+  "tokenizer_class": "PreTrainedTokenizerFast"
+}
diff --git a/checkpoint-1842/trainer_state.json b/checkpoint-1842/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..7e26df15734e91444daba55706b1d7ecd59c3621
--- /dev/null
+++ b/checkpoint-1842/trainer_state.json
@@ -0,0 +1,1385 @@
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diff --git a/checkpoint-205/README.md b/checkpoint-205/README.md
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+---
+base_model: Salesforce/Llama-xLAM-2-8b-fc-r
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:Salesforce/Llama-xLAM-2-8b-fc-r
+- lora
+- sft
+- transformers
+- trl
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.17.1
\ No newline at end of file
diff --git a/checkpoint-205/adapter_config.json b/checkpoint-205/adapter_config.json
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+}
\ No newline at end of file
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+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "additional_special_tokens": [
+    "<|eot_id|>",
+    "<|eom_id|>"
+  ],
+  "bos_token": "<|begin_of_text|>",
+  "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n    {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n    {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not tools is defined %}\n    {%- set tools = none %}\n{%- endif %}\n\n{#- Extract system message #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if messages[0]['role'] == 'system' %}\n    {%- set system_message = messages[0]['content'] | trim %}\n    {%- set messages = messages[1:] %}\n    {{- system_message + \"\\n\" }}\n{%- else %}\n    {%- set system_message = \"You are a helpful assistant that can use tools. You are developed by Salesforce xLAM team.\" %}\n    {% set format_instruction %}You have access to a set of tools. When using tools, make calls in a single JSON array: \n\n[{\"name\": \"tool_call_name\", \"arguments\": {\"arg1\": \"value1\", \"arg2\": \"value2\"}}, ... (additional parallel tool calls as needed)]\n\nIf no tool is suitable, state that explicitly. If the user's input lacks required parameters, ask for clarification. Do not interpret or respond until tool results are returned. Once they are available, process them or make additional calls if needed. For tasks that don't require tools, such as casual conversation or general advice, respond directly in plain text. The available tools are:{% endset %}\n    {{- system_message + \"\\n\" }}\n    {%- if tools is not none %}\n        {{- format_instruction + \"\\n\\n\" }}\n    {%- endif %}\n{%- endif %}\n\n\n{%- if tools is not none %}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\\n\\n\" }}\n    {%- endfor %}\n{%- endif %}\n{{- \"<|eot_id|>\" }}\n\n{%- for message in messages %}\n    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n    {%- elif 'tool_calls' in message %}\n        {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n        {%- if message['tool_calls'] %}\n            {{- \"[\" }}\n            {%- for tool_call_function in message.tool_calls %}\n                {%- set tool_call = tool_call_function.function %}\n                {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n                {{- '\"arguments\": ' }}\n                {{- tool_call.arguments | tojson }}\n                {{- \"}\" }}\n                {%- if not loop.last %}\n                    {{- \", \" }}\n                {%- endif %}\n            {%- endfor %}\n            {{- \"]\" }}\n            {{- \"<|eot_id|>\" }}\n        {%- elif message['content'] %}\n            {{- message['content'] | trim + '<|eot_id|>' }}\n        {%- else %}\n            {{- \"[]\\n\" + '<|eot_id|>' }}\n        {%- endif %}\n    {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n        {{- \"<|start_header_id|>\" + \"ipython\" + \"<|end_header_id|>\\n\\n\" }}\n        {%- set content = message[\"content\"] %}\n        {%- if content is mapping or (content is iterable and content is not string) %}\n            {{- content | tojson }}\n        {%- else %}\n            {{- content }}\n        {%- endif %}\n        {{- \"<|eot_id|>\" }}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}",
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|eot_id|>",
+  "extra_special_tokens": {},
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 16384,
+  "pad_token": "<|eot_id|>",
+  "padding_side": "right",
+  "split_special_tokens": false,
+  "tokenizer_class": "PreTrainedTokenizerFast"
+}
diff --git a/checkpoint-205/trainer_state.json b/checkpoint-205/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..32cf0b098cbb4bacb27e9b5fc8477df52887dca0
--- /dev/null
+++ b/checkpoint-205/trainer_state.json
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+{
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+  "global_step": 205,
+  "is_hyper_param_search": false,
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+  "is_world_process_zero": true,
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+  "logging_steps": 10,
+  "max_steps": 1842,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 3,
+  "save_steps": 205,
+  "stateful_callbacks": {
+    "TrainerControl": {
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+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
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+  "trial_params": null
+}
diff --git a/checkpoint-205/training_args.bin b/checkpoint-205/training_args.bin
new file mode 100644
index 0000000000000000000000000000000000000000..2245771e9af5d2e40208df60ece818e12dad2609
--- /dev/null
+++ b/checkpoint-205/training_args.bin
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fba26e4087d6f0d4a22136ed77169fa2a327b3a4a3accd6168e4c2098fb9b7b6
+size 5624
diff --git a/checkpoint-410/README.md b/checkpoint-410/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..20c165c7feaa880a18e0662941a5b246a698be2e
--- /dev/null
+++ b/checkpoint-410/README.md
@@ -0,0 +1,209 @@
+---
+base_model: Salesforce/Llama-xLAM-2-8b-fc-r
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:Salesforce/Llama-xLAM-2-8b-fc-r
+- lora
+- sft
+- transformers
+- trl
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.17.1
\ No newline at end of file
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\ No newline at end of file
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+  "bos_token": "<|begin_of_text|>",
+  "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n    {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n    {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not tools is defined %}\n    {%- set tools = none %}\n{%- endif %}\n\n{#- Extract system message #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if messages[0]['role'] == 'system' %}\n    {%- set system_message = messages[0]['content'] | trim %}\n    {%- set messages = messages[1:] %}\n    {{- system_message + \"\\n\" }}\n{%- else %}\n    {%- set system_message = \"You are a helpful assistant that can use tools. You are developed by Salesforce xLAM team.\" %}\n    {% set format_instruction %}You have access to a set of tools. When using tools, make calls in a single JSON array: \n\n[{\"name\": \"tool_call_name\", \"arguments\": {\"arg1\": \"value1\", \"arg2\": \"value2\"}}, ... (additional parallel tool calls as needed)]\n\nIf no tool is suitable, state that explicitly. If the user's input lacks required parameters, ask for clarification. Do not interpret or respond until tool results are returned. Once they are available, process them or make additional calls if needed. For tasks that don't require tools, such as casual conversation or general advice, respond directly in plain text. The available tools are:{% endset %}\n    {{- system_message + \"\\n\" }}\n    {%- if tools is not none %}\n        {{- format_instruction + \"\\n\\n\" }}\n    {%- endif %}\n{%- endif %}\n\n\n{%- if tools is not none %}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\\n\\n\" }}\n    {%- endfor %}\n{%- endif %}\n{{- \"<|eot_id|>\" }}\n\n{%- for message in messages %}\n    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n    {%- elif 'tool_calls' in message %}\n        {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n        {%- if message['tool_calls'] %}\n            {{- \"[\" }}\n            {%- for tool_call_function in message.tool_calls %}\n                {%- set tool_call = tool_call_function.function %}\n                {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n                {{- '\"arguments\": ' }}\n                {{- tool_call.arguments | tojson }}\n                {{- \"}\" }}\n                {%- if not loop.last %}\n                    {{- \", \" }}\n                {%- endif %}\n            {%- endfor %}\n            {{- \"]\" }}\n            {{- \"<|eot_id|>\" }}\n        {%- elif message['content'] %}\n            {{- message['content'] | trim + '<|eot_id|>' }}\n        {%- else %}\n            {{- \"[]\\n\" + '<|eot_id|>' }}\n        {%- endif %}\n    {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n        {{- \"<|start_header_id|>\" + \"ipython\" + \"<|end_header_id|>\\n\\n\" }}\n        {%- set content = message[\"content\"] %}\n        {%- if content is mapping or (content is iterable and content is not string) %}\n            {{- content | tojson }}\n        {%- else %}\n            {{- content }}\n        {%- endif %}\n        {{- \"<|eot_id|>\" }}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}",
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|eot_id|>",
+  "extra_special_tokens": {},
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 16384,
+  "pad_token": "<|eot_id|>",
+  "padding_side": "right",
+  "split_special_tokens": false,
+  "tokenizer_class": "PreTrainedTokenizerFast"
+}
diff --git a/checkpoint-410/trainer_state.json b/checkpoint-410/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..607805bec17b72bcdb212ba8c831c3a4dc029fbe
--- /dev/null
+++ b/checkpoint-410/trainer_state.json
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+{
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+  "max_steps": 1842,
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+  "num_train_epochs": 3,
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+  "stateful_callbacks": {
+    "TrainerControl": {
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+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
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+}
diff --git a/checkpoint-410/training_args.bin b/checkpoint-410/training_args.bin
new file mode 100644
index 0000000000000000000000000000000000000000..2245771e9af5d2e40208df60ece818e12dad2609
--- /dev/null
+++ b/checkpoint-410/training_args.bin
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+version https://git-lfs.github.com/spec/v1
+oid sha256:fba26e4087d6f0d4a22136ed77169fa2a327b3a4a3accd6168e4c2098fb9b7b6
+size 5624
diff --git a/checkpoint-615/README.md b/checkpoint-615/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..20c165c7feaa880a18e0662941a5b246a698be2e
--- /dev/null
+++ b/checkpoint-615/README.md
@@ -0,0 +1,209 @@
+---
+base_model: Salesforce/Llama-xLAM-2-8b-fc-r
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:Salesforce/Llama-xLAM-2-8b-fc-r
+- lora
+- sft
+- transformers
+- trl
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.17.1
\ No newline at end of file
diff --git a/checkpoint-615/adapter_config.json b/checkpoint-615/adapter_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..9eda25bff7c128105e91aa1a00507aaa31dd53fd
--- /dev/null
+++ b/checkpoint-615/adapter_config.json
@@ -0,0 +1,39 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "Salesforce/Llama-xLAM-2-8b-fc-r",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "v_proj",
+    "k_proj",
+    "o_proj"
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+  "target_parameters": null,
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+  "additional_special_tokens": [
+    "<|eot_id|>",
+    "<|eom_id|>"
+  ],
+  "bos_token": "<|begin_of_text|>",
+  "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n    {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n    {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not tools is defined %}\n    {%- set tools = none %}\n{%- endif %}\n\n{#- Extract system message #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if messages[0]['role'] == 'system' %}\n    {%- set system_message = messages[0]['content'] | trim %}\n    {%- set messages = messages[1:] %}\n    {{- system_message + \"\\n\" }}\n{%- else %}\n    {%- set system_message = \"You are a helpful assistant that can use tools. You are developed by Salesforce xLAM team.\" %}\n    {% set format_instruction %}You have access to a set of tools. When using tools, make calls in a single JSON array: \n\n[{\"name\": \"tool_call_name\", \"arguments\": {\"arg1\": \"value1\", \"arg2\": \"value2\"}}, ... (additional parallel tool calls as needed)]\n\nIf no tool is suitable, state that explicitly. If the user's input lacks required parameters, ask for clarification. Do not interpret or respond until tool results are returned. Once they are available, process them or make additional calls if needed. For tasks that don't require tools, such as casual conversation or general advice, respond directly in plain text. The available tools are:{% endset %}\n    {{- system_message + \"\\n\" }}\n    {%- if tools is not none %}\n        {{- format_instruction + \"\\n\\n\" }}\n    {%- endif %}\n{%- endif %}\n\n\n{%- if tools is not none %}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\\n\\n\" }}\n    {%- endfor %}\n{%- endif %}\n{{- \"<|eot_id|>\" }}\n\n{%- for message in messages %}\n    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n    {%- elif 'tool_calls' in message %}\n        {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n        {%- if message['tool_calls'] %}\n            {{- \"[\" }}\n            {%- for tool_call_function in message.tool_calls %}\n                {%- set tool_call = tool_call_function.function %}\n                {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n                {{- '\"arguments\": ' }}\n                {{- tool_call.arguments | tojson }}\n                {{- \"}\" }}\n                {%- if not loop.last %}\n                    {{- \", \" }}\n                {%- endif %}\n            {%- endfor %}\n            {{- \"]\" }}\n            {{- \"<|eot_id|>\" }}\n        {%- elif message['content'] %}\n            {{- message['content'] | trim + '<|eot_id|>' }}\n        {%- else %}\n            {{- \"[]\\n\" + '<|eot_id|>' }}\n        {%- endif %}\n    {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n        {{- \"<|start_header_id|>\" + \"ipython\" + \"<|end_header_id|>\\n\\n\" }}\n        {%- set content = message[\"content\"] %}\n        {%- if content is mapping or (content is iterable and content is not string) %}\n            {{- content | tojson }}\n        {%- else %}\n            {{- content }}\n        {%- endif %}\n        {{- \"<|eot_id|>\" }}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}",
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|eot_id|>",
+  "extra_special_tokens": {},
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 16384,
+  "pad_token": "<|eot_id|>",
+  "padding_side": "right",
+  "split_special_tokens": false,
+  "tokenizer_class": "PreTrainedTokenizerFast"
+}
diff --git a/checkpoint-615/trainer_state.json b/checkpoint-615/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..fb381f76f3cf8575df696f4b561018668e894030
--- /dev/null
+++ b/checkpoint-615/trainer_state.json
@@ -0,0 +1,484 @@
+{
+  "best_metric": 0.2388339340686798,
+  "best_model_checkpoint": "./xlam_lora_new_ete_over_size_3epoch_multi_mix/checkpoint-615",
+  "epoch": 1.0011700666429262,
+  "eval_steps": 205,
+  "global_step": 615,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
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diff --git a/checkpoint-820/README.md b/checkpoint-820/README.md
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+---
+base_model: Salesforce/Llama-xLAM-2-8b-fc-r
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:Salesforce/Llama-xLAM-2-8b-fc-r
+- lora
+- sft
+- transformers
+- trl
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.17.1
\ No newline at end of file
diff --git a/checkpoint-820/adapter_config.json b/checkpoint-820/adapter_config.json
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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "Salesforce/Llama-xLAM-2-8b-fc-r",
+  "bias": "none",
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+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "v_proj",
+    "k_proj",
+    "o_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}
\ No newline at end of file
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+  "additional_special_tokens": [
+    "<|eot_id|>",
+    "<|eom_id|>"
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+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|eot_id|>",
+  "extra_special_tokens": {},
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 16384,
+  "pad_token": "<|eot_id|>",
+  "padding_side": "right",
+  "split_special_tokens": false,
+  "tokenizer_class": "PreTrainedTokenizerFast"
+}
diff --git a/checkpoint-820/trainer_state.json b/checkpoint-820/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..e1bc05048e9c8d17fd3facc4e0696e16e66217ac
--- /dev/null
+++ b/checkpoint-820/trainer_state.json
@@ -0,0 +1,639 @@
+{
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+  "best_model_checkpoint": "./xlam_lora_new_ete_over_size_3epoch_multi_mix/checkpoint-820",
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+  "global_step": 820,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
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+      "lstrip": false,
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+      "rstrip": false,
+      "single_word": false,
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+    }
+  },
+  "additional_special_tokens": [
+    "<|eot_id|>",
+    "<|eom_id|>"
+  ],
+  "bos_token": "<|begin_of_text|>",
+  "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n    {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n    {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not tools is defined %}\n    {%- set tools = none %}\n{%- endif %}\n\n{#- Extract system message #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if messages[0]['role'] == 'system' %}\n    {%- set system_message = messages[0]['content'] | trim %}\n    {%- set messages = messages[1:] %}\n    {{- system_message + \"\\n\" }}\n{%- else %}\n    {%- set system_message = \"You are a helpful assistant that can use tools. You are developed by Salesforce xLAM team.\" %}\n    {% set format_instruction %}You have access to a set of tools. When using tools, make calls in a single JSON array: \n\n[{\"name\": \"tool_call_name\", \"arguments\": {\"arg1\": \"value1\", \"arg2\": \"value2\"}}, ... (additional parallel tool calls as needed)]\n\nIf no tool is suitable, state that explicitly. If the user's input lacks required parameters, ask for clarification. Do not interpret or respond until tool results are returned. Once they are available, process them or make additional calls if needed. For tasks that don't require tools, such as casual conversation or general advice, respond directly in plain text. The available tools are:{% endset %}\n    {{- system_message + \"\\n\" }}\n    {%- if tools is not none %}\n        {{- format_instruction + \"\\n\\n\" }}\n    {%- endif %}\n{%- endif %}\n\n\n{%- if tools is not none %}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\\n\\n\" }}\n    {%- endfor %}\n{%- endif %}\n{{- \"<|eot_id|>\" }}\n\n{%- for message in messages %}\n    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n    {%- elif 'tool_calls' in message %}\n        {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n        {%- if message['tool_calls'] %}\n            {{- \"[\" }}\n            {%- for tool_call_function in message.tool_calls %}\n                {%- set tool_call = tool_call_function.function %}\n                {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n                {{- '\"arguments\": ' }}\n                {{- tool_call.arguments | tojson }}\n                {{- \"}\" }}\n                {%- if not loop.last %}\n                    {{- \", \" }}\n                {%- endif %}\n            {%- endfor %}\n            {{- \"]\" }}\n            {{- \"<|eot_id|>\" }}\n        {%- elif message['content'] %}\n            {{- message['content'] | trim + '<|eot_id|>' }}\n        {%- else %}\n            {{- \"[]\\n\" + '<|eot_id|>' }}\n        {%- endif %}\n    {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n        {{- \"<|start_header_id|>\" + \"ipython\" + \"<|end_header_id|>\\n\\n\" }}\n        {%- set content = message[\"content\"] %}\n        {%- if content is mapping or (content is iterable and content is not string) %}\n            {{- content | tojson }}\n        {%- else %}\n            {{- content }}\n        {%- endif %}\n        {{- \"<|eot_id|>\" }}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}",
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|eot_id|>",
+  "extra_special_tokens": {},
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 16384,
+  "pad_token": "<|eot_id|>",
+  "padding_side": "right",
+  "split_special_tokens": false,
+  "tokenizer_class": "PreTrainedTokenizerFast"
+}
diff --git a/plot_loss_from_trainer_state.py b/plot_loss_from_trainer_state.py
new file mode 100644
index 0000000000000000000000000000000000000000..eaf442644d02d8625f8186aa6d050495712cd2f9
--- /dev/null
+++ b/plot_loss_from_trainer_state.py
@@ -0,0 +1,160 @@
+# -*- coding: utf-8 -*-
+"""
+Usage:
+  python plot_loss_from_trainer_state.py --input trainer_state.json --outdir ./plots \
+         --checkpoint_steps 263,526,789,1052
+
+功能:
+- Curve: 黃橘色實線
+- Grid: x,y 虛線
+- Epoch markers: 藍色虛線 + EpochN 標籤（含最後一個 epoch）
+- Checkpoints: 藍色小圓點（線性插值；超出範圍時使用端點值，並自動擴張 x 軸確保能看見）
+"""
+import json, argparse
+from pathlib import Path
+import matplotlib.pyplot as plt
+import numpy as np
+
+YELLOW_ORANGE = "#d58f00"
+BLUE = "#1f77b4"
+
+def find_epoch_boundaries(log_items):
+    """找到每個 epoch 邊界 (包含最後一個)"""
+    boundaries = []
+    prev_epoch_int = None
+    seen = set()
+    last_step, last_epoch = None, None
+    for it in log_items:
+        step = it.get("step")
+        ep = it.get("epoch")
+        if step is None or ep is None:
+            continue
+        last_step, last_epoch = step, ep
+        ep_int = int(ep)
+        if prev_epoch_int is None:
+            prev_epoch_int = ep_int
+            continue
+        if ep_int != prev_epoch_int:
+            if (step, ep_int) not in seen and ep_int >= 1:
+                boundaries.append((step, ep_int))
+                seen.add((step, ep_int))
+            prev_epoch_int = ep_int
+    # 最後一個 epoch 也補上
+    if last_step is not None and last_epoch is not None:
+        ep_final = int(float(last_epoch)) + 1
+        if (last_step, ep_final) not in seen:
+            boundaries.append((last_step, ep_final))
+    boundaries.sort(key=lambda x: x[0])
+    return boundaries
+
+def plot_series(x, y, xlabel, ylabel, title, outpath,
+                epoch_marks=None, checkpoint_steps=None,
+                color=YELLOW_ORANGE, linestyle='-'):
+    fig = plt.figure(figsize=(10,6))
+    ax = fig.add_subplot(111)
+    ax.plot(x, y, color=color, linestyle=linestyle, linewidth=2)
+
+    # 標記 checkpoint 藍點（線性插值；邊界外使用端點值）
+    extra_x = []
+    if checkpoint_steps:
+        for s in checkpoint_steps:
+            y_interp = np.interp(s, x, y, left=y[0], right=y[-1])
+            ax.plot(s, y_interp, marker='o', color=BLUE, markersize=6)
+            extra_x.append(s)
+
+    # === 計算 x 範圍時把 epoch 標線也納入，並加右側 padding ===
+    xmin = 0
+    all_x_candidates = [max(x)]
+    if extra_x:
+        all_x_candidates.append(max(extra_x))
+    if epoch_marks:
+        # 把所有 epoch 標線的 step 納入考量
+        ep_steps = [s for (s, _) in epoch_marks]
+        if ep_steps:
+            all_x_candidates.append(max(ep_steps))
+
+    xmax_base = max(all_x_candidates) if all_x_candidates else x[-1]
+
+    # 右邊加一點 margin，避免剛好貼齊看不到線
+    span = max(xmax_base - xmin, 1.0)
+    right_pad = max(1.0, 0.02 * span)   # 至少 +1 step 或 2% 寬度
+    ax.set_xlim(left=xmin, right=xmax_base + right_pad)
+
+    # y 仍從 0 起
+    ax.set_ylim(bottom=0)
+
+    # 虛線格線
+    ax.grid(True, which='major', axis='both', linestyle='--', linewidth=0.8, alpha=0.6)
+
+    # epoch 標記 (藍色虛線)
+    if epoch_marks:
+        for step, ep in epoch_marks:
+            ax.axvline(x=step, color=BLUE, linestyle='--', linewidth=1.2)
+            ymax = ax.get_ylim()[1]
+            ax.text(step, ymax*0.98, f'Epoch{ep}', rotation=90,
+                    va='top', ha='right', fontsize=8, color=BLUE)
+
+    # label & look（放到最後避免被 set_xlim/set_ylim 影響）
+    ax.set_xlabel(xlabel); ax.set_ylabel(ylabel); ax.set_title(title)
+    ax.spines['left'].set_linewidth(2); ax.spines['bottom'].set_linewidth(2)
+    ax.spines['right'].set_visible(False); ax.spines['top'].set_visible(False)
+
+    fig.savefig(outpath, bbox_inches="tight")
+    plt.close(fig)
+
+
+def main():
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--input", required=True, help="Path to trainer_state.json")
+    ap.add_argument("--outdir", default="./plots", help="Directory to save PNGs")
+    ap.add_argument("--no_epoch_marks", action="store_true", help="Disable vertical epoch markers")
+    ap.add_argument("--checkpoint_steps", default="", help="Comma-separated steps (e.g., 100,200,500)")
+    args = ap.parse_args()
+
+    src = Path(args.input)
+    with open(src, "r", encoding="utf-8") as f:
+        state = json.load(f)
+
+    log = state.get("log_history", state.get("logs", []))
+
+    steps, train_losses = [], []
+    eval_steps, eval_losses = [], []
+    lr_steps, lrs = [], []
+
+    for item in log:
+        step = item.get("step")
+        if step is None: 
+            continue
+        if "loss" in item:
+            steps.append(step); train_losses.append(item["loss"])
+        if "eval_loss" in item:
+            eval_steps.append(step); eval_losses.append(item["eval_loss"])
+        if "learning_rate" in item:
+            lr_steps.append(step); lrs.append(item["learning_rate"])
+
+    outdir = Path(args.outdir); outdir.mkdir(parents=True, exist_ok=True)
+
+    epoch_marks = None if args.no_epoch_marks else find_epoch_boundaries(log)
+    # 允許空白與混合格式
+    raw = [s.strip() for s in args.checkpoint_steps.replace("，", ",").split(",") if s.strip()]
+    checkpoint_steps = []
+    for s in raw:
+        try:
+            checkpoint_steps.append(int(float(s)))
+        except:
+            pass
+
+    if steps and train_losses:
+        plot_series(steps, train_losses, "Step", "Training Loss", "Training Loss vs Step",
+                    outdir / "loss_curve.png", epoch_marks=epoch_marks, checkpoint_steps=checkpoint_steps)
+    if eval_steps and eval_losses:
+        plot_series(eval_steps, eval_losses, "Step", "Eval Loss", "Eval Loss vs Step",
+                    outdir / "eval_loss_curve.png", epoch_marks=epoch_marks, checkpoint_steps=checkpoint_steps)
+    if lr_steps and lrs:
+        plot_series(lr_steps, lrs, "Step", "Learning Rate", "Learning Rate vs Step",
+                    outdir / "lr_curve.png", epoch_marks=epoch_marks, checkpoint_steps=checkpoint_steps)
+
+    print(f"Saved plots to: {outdir.resolve()}")
+
+if __name__ == "__main__":
+    main()
diff --git a/plots/.ipynb_checkpoints/loss_curve-checkpoint.png b/plots/.ipynb_checkpoints/loss_curve-checkpoint.png
new file mode 100644
index 0000000000000000000000000000000000000000..e783683efc49a0ab1f3eab80791efe9a8cffa913
Binary files /dev/null and b/plots/.ipynb_checkpoints/loss_curve-checkpoint.png differ
diff --git a/plots/eval_loss_curve.png b/plots/eval_loss_curve.png
new file mode 100644
index 0000000000000000000000000000000000000000..112bd60f0c6b420ac9dc244f8410e21e6b4857ac
Binary files /dev/null and b/plots/eval_loss_curve.png differ
diff --git a/plots/loss_curve.png b/plots/loss_curve.png
new file mode 100644
index 0000000000000000000000000000000000000000..e783683efc49a0ab1f3eab80791efe9a8cffa913
Binary files /dev/null and b/plots/loss_curve.png differ
diff --git a/plots/lr_curve.png b/plots/lr_curve.png
new file mode 100644
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diff --git a/runs/Oct15_18-23-48_pytorch-deployment-1978518505210822657-79b6d97bc-tl4dj/events.out.tfevents.1760552638.pytorch-deployment-1978518505210822657-79b6d97bc-tl4dj.2027.0 b/runs/Oct15_18-23-48_pytorch-deployment-1978518505210822657-79b6d97bc-tl4dj/events.out.tfevents.1760552638.pytorch-deployment-1978518505210822657-79b6d97bc-tl4dj.2027.0
new file mode 100644
index 0000000000000000000000000000000000000000..fd9fc908b4b8f60b49434ade93474c6403eb7826
--- /dev/null
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@@ -0,0 +1,3 @@
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diff --git a/special_tokens_map.json b/special_tokens_map.json
new file mode 100644
index 0000000000000000000000000000000000000000..1c69f55fd7bb10288d16d4c76497e21e25adfe4f
--- /dev/null
+++ b/special_tokens_map.json
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+{
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+    "<|eot_id|>",
+    "<|eom_id|>"
+  ],
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diff --git a/tokenizer.json b/tokenizer.json
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index 0000000000000000000000000000000000000000..1c1d8d5c9024994f1d3b00f9662b8dd89ca13cf2
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diff --git a/tokenizer_config.json b/tokenizer_config.json
new file mode 100644
index 0000000000000000000000000000000000000000..3c3fc3b2c234aa8b39e8ee01e3ee9e6fe54a2a1f
--- /dev/null
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+  "additional_special_tokens": [
+    "<|eot_id|>",
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+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|eot_id|>",
+  "extra_special_tokens": {},
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 16384,
+  "pad_token": "<|eot_id|>",
+  "padding_side": "right",
+  "split_special_tokens": false,
+  "tokenizer_class": "PreTrainedTokenizerFast"
+}
diff --git a/trainer_state.json b/trainer_state.json
new file mode 100644
index 0000000000000000000000000000000000000000..9eb2df5967291622bda2a55e7ef0214149b331d4
--- /dev/null
+++ b/trainer_state.json
@@ -0,0 +1,1394 @@
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--- /dev/null
+++ b/training_meta.json
@@ -0,0 +1,25 @@
+{
+  "num_samples_train": 19657,
+  "world_size": 1,
+  "effective_batch_size": 32,
+  "steps_per_epoch": 615,
+  "save_steps": 205,
+  "saves_per_epoch": 3,
+  "total_steps_est": 1845,
+  "approx_ckpts": 9,
+  "target_modules": [
+    "q_proj",
+    "k_proj",
+    "v_proj",
+    "o_proj"
+  ],
+  "lora_r": 16,
+  "lora_alpha": 32,
+  "lora_dropout": 0.05,
+  "response_template": "<|start_header_id|>assistant<|end_header_id|>",
+  "use_max_len": 2560,
+  "label_all_assistant": true,
+  "skip_tool_only_assistant": false,
+  "assistant_tag": "<|start_header_id|>assistant<|end_header_id|>",
+  "tool_use_token": "<|use_tool|>"
+}
\ No newline at end of file