diff --git a/.gitattributes b/.gitattributes index a6344aac8c09253b3b630fb776ae94478aa0275b..6464d9521532e1f5376f1f3e0948ecb2998a5d04 100644 --- a/.gitattributes +++ b/.gitattributes @@ -33,3 +33,8 @@ 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-150/tokenizer.json filter=lfs diff=lfs merge=lfs -text +checkpoint-200/tokenizer.json filter=lfs diff=lfs merge=lfs -text +checkpoint-210/tokenizer.json filter=lfs diff=lfs merge=lfs -text +final_model/tokenizer.json filter=lfs diff=lfs merge=lfs -text +lora_adapters/tokenizer.json filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000000000000000000000000000000000000..752bf84df03d92b92de896f70eff55772a0fa505 --- /dev/null +++ b/README.md @@ -0,0 +1,179 @@ +--- +language: +- vi +- en +license: apache-2.0 +tags: +- llm-judge +- training-checkpoint +- lora +- unsloth +--- + +# llm-judge-full-backup + +Full training folder backup - ToΓ n bα»™ checkpoints vΓ  models. + +## πŸ“‚ CαΊ₯u trΓΊc Folder +``` +train_llm_judge_v2/ +β”œβ”€β”€ checkpoint-150/ # Checkpoint tαΊ‘i step 150 +β”œβ”€β”€ checkpoint-200/ # Checkpoint tαΊ‘i step 200 +β”œβ”€β”€ checkpoint-210/ # Checkpoint tαΊ‘i step 210 +β”œβ”€β”€ final_model/ # Model cuα»‘i cΓΉng (merged) +β”œβ”€β”€ lora_adapters/ # LoRA adapters +β”œβ”€β”€ README.md +β”œβ”€β”€ zero_shot_metrics.json +└── zero_shot_results.csv +``` + +## πŸš€ Sα»­ Dα»₯ng + +### 1️⃣ Clone Repo +```bash +git lfs install +git clone https://huggingface.co/ImNotTam/llm-judge-full-backup +cd llm-judge-full-backup +``` + +### 2️⃣ Load LoRA Adapters (NhαΊΉ nhαΊ₯t - khuyαΊΏn nghα»‹) +```python +from unsloth import FastLanguageModel + +model, tokenizer = FastLanguageModel.from_pretrained( + model_name="ImNotTam/llm-judge-full-backup", + subfolder="lora_adapters", + max_seq_length=2048, + dtype=None, + load_in_4bit=True, +) + +# Enable inference mode +FastLanguageModel.for_inference(model) + +# Test +prompt = "ĐÑnh giΓ‘ response nΓ y..." +inputs = tokenizer(prompt, return_tensors="pt").to("cuda") +outputs = model.generate(**inputs, max_new_tokens=256) +print(tokenizer.decode(outputs[0], skip_special_tokens=True)) +``` + +### 3️⃣ Load Final Model +```python +from transformers import AutoModelForCausalLM, AutoTokenizer + +model = AutoModelForCausalLM.from_pretrained( + "ImNotTam/llm-judge-full-backup", + subfolder="final_model", + device_map="auto", + torch_dtype="auto" +) +tokenizer = AutoTokenizer.from_pretrained("ImNotTam/llm-judge-full-backup", subfolder="final_model") + +# Inference +inputs = tokenizer("Your prompt", return_tensors="pt").to("cuda") +outputs = model.generate(**inputs) +print(tokenizer.decode(outputs[0])) +``` + +### 4️⃣ Resume Training tα»« Checkpoint +```python +from transformers import Trainer, TrainingArguments + +# Load checkpoint muα»‘n resume +model = AutoModelForCausalLM.from_pretrained( + "ImNotTam/llm-judge-full-backup", + subfolder="checkpoint-210", # Chọn checkpoint + device_map="auto" +) + +# Continue training +trainer = Trainer( + model=model, + args=TrainingArguments( + output_dir="./continue_training", + # ... your training args + ), +) +trainer.train(resume_from_checkpoint=True) +``` + +### 5️⃣ Fine-tune TiαΊΏp tα»« LoRA Adapter +```python +from unsloth import FastLanguageModel +from trl import SFTTrainer + +# Load LoRA adapter +model, tokenizer = FastLanguageModel.from_pretrained( + model_name="ImNotTam/llm-judge-full-backup", + subfolder="lora_adapters", + max_seq_length=2048, + dtype=None, + load_in_4bit=True, +) + +# Add LoRA config để train tiαΊΏp +model = FastLanguageModel.get_peft_model( + model, + r=16, + target_modules=["q_proj", "k_proj", "v_proj", "o_proj", + "gate_proj", "up_proj", "down_proj"], + lora_alpha=16, + lora_dropout=0, + bias="none", + use_gradient_checkpointing="unsloth", +) + +# Train vα»›i data mα»›i +trainer = SFTTrainer( + model=model, + tokenizer=tokenizer, + train_dataset=your_new_dataset, + # ... training args +) +trainer.train() +``` + +### 6️⃣ Xem Metrics vΓ  Results +```python +import json +import pandas as pd + +# Load metrics +with open("zero_shot_metrics.json", "r") as f: + metrics = json.load(f) +print("πŸ“Š Metrics:", metrics) + +# Load results +results = pd.read_csv("zero_shot_results.csv") +print("\nπŸ“ˆ Results:") +print(results.head()) +``` + +## πŸ“‹ Nα»™i Dung Repo + +| Folder/File | MΓ΄ tαΊ£ | KΓ­ch thΖ°α»›c | +|-------------|-------|------------| +| `lora_adapters/` | LoRA adapters (nhαΊΉ) | ~50-100 MB | +| `final_model/` | Model merged Δ‘αΊ§y Δ‘α»§ | ~4-8 GB | +| `checkpoint-150/` | Training checkpoint | ~4-8 GB | +| `checkpoint-200/` | Training checkpoint | ~4-8 GB | +| `checkpoint-210/` | Training checkpoint | ~4-8 GB | +| `zero_shot_metrics.json` | Evaluation metrics | <1 MB | +| `zero_shot_results.csv` | Detailed results | <1 MB | + +## πŸ’‘ KhuyαΊΏn Nghα»‹ + +- **Inference nhanh:** DΓΉng `lora_adapters/` +- **Production:** DΓΉng `final_model/` +- **Train tiαΊΏp:** Load `lora_adapters/` + add LoRA config +- **Resume training:** Load checkpoint cα»₯ thể + +## πŸ“¦ Requirements +```bash +pip install unsloth transformers torch trl +``` + +## πŸ“„ License + +Apache 2.0 diff --git a/checkpoint-150/README.md b/checkpoint-150/README.md new file mode 100644 index 0000000000000000000000000000000000000000..997dfea7b8b95c2838e714919b08c184b7abce8b --- /dev/null +++ b/checkpoint-150/README.md @@ -0,0 +1,210 @@ +--- +base_model: unsloth/medgemma-4b-it-unsloth-bnb-4bit +library_name: peft +pipeline_tag: text-generation +tags: +- base_model:adapter:unsloth/medgemma-4b-it-unsloth-bnb-4bit +- lora +- sft +- transformers +- trl +- unsloth +--- + +# Model Card for Model ID + + + + + +## Model Details + +### Model Description + + + + + +- **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] + + + +- **Repository:** [More Information Needed] +- **Paper [optional]:** [More Information Needed] +- **Demo [optional]:** [More Information Needed] + +## Uses + + + +### Direct Use + + + +[More Information Needed] + +### Downstream Use [optional] + + + +[More Information Needed] + +### Out-of-Scope Use + + + +[More Information Needed] + +## Bias, Risks, and Limitations + + + +[More Information Needed] + +### Recommendations + + + +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 + + + +[More Information Needed] + +### Training Procedure + + + +#### Preprocessing [optional] + +[More Information Needed] + + +#### Training Hyperparameters + +- **Training regime:** [More Information Needed] + +#### Speeds, Sizes, Times [optional] + + + +[More Information Needed] + +## Evaluation + + + +### Testing Data, Factors & Metrics + +#### Testing Data + + + +[More Information Needed] + +#### Factors + + + +[More Information Needed] + +#### Metrics + + + +[More Information Needed] + +### Results + +[More Information Needed] + +#### Summary + + + +## Model Examination [optional] + + + +[More Information Needed] + +## Environmental Impact + + + +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] + + + +**BibTeX:** + +[More Information Needed] + +**APA:** + +[More Information Needed] + +## Glossary [optional] + + + +[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-150/adapter_config.json b/checkpoint-150/adapter_config.json new file mode 100644 index 0000000000000000000000000000000000000000..fbeea5aa6bdfe2c831eaf0480ea1d18180372047 --- /dev/null +++ b/checkpoint-150/adapter_config.json @@ -0,0 +1,38 @@ +{ + "alpha_pattern": {}, + "auto_mapping": { + "base_model_class": "Gemma3ForConditionalGeneration", + "parent_library": "transformers.models.gemma3.modeling_gemma3", + "unsloth_fixed": true + }, + "base_model_name_or_path": "unsloth/medgemma-4b-it-unsloth-bnb-4bit", + "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": 64, + "lora_bias": false, + "lora_dropout": 0.05, + "megatron_config": null, + "megatron_core": "megatron.core", + "modules_to_save": null, + "peft_type": "LORA", + 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= "" -%} + {%- set loop_messages = messages -%} +{%- endif -%} +{%- for message in loop_messages -%} + {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%} + {{ raise_exception("Conversation roles must alternate user/assistant/user/assistant/...") }} + {%- endif -%} + {%- if (message['role'] == 'assistant') -%} + {%- set role = "model" -%} + {%- else -%} + {%- set role = message['role'] -%} + {%- endif -%} + {{ '' + role + ' +' + (first_user_prefix if loop.first else "") }} + {%- if message['content'] is string -%} + {{ message['content'] | trim }} + {%- elif message['content'] is iterable -%} + {%- for item in message['content'] -%} + {%- if item['type'] == 'image' -%} + {{ '' }} + {%- elif item['type'] == 'text' -%} + {{ item['text'] | trim }} + {%- endif -%} + {%- endfor -%} + {%- else -%} + {{ raise_exception("Invalid content type") }} + {%- endif -%} + {{ ' +' }} +{%- endfor -%} +{%- if add_generation_prompt -%} + {{'model +'}} +{%- endif -%} diff --git 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