File size: 3,304 Bytes
03423b0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 |
---
library_name: peft
license: cc-by-nc-4.0
base_model: CohereLabs/aya-expanse-8b
tags:
- generated_from_trainer
datasets:
- matrixportal/turkish_medical_alpaca
model-index:
- name: outputs/lora-out
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<details><summary>See axolotl config</summary>
axolotl version: `0.8.1`
```yaml
adapter: qlora
base_model: CohereLabs/aya-expanse-8b
bf16: auto
dataset_prepared_path: last_run_prepared
datasets:
- path: matrixportal/turkish_medical_alpaca
type: alpaca
debug: null
deepspeed: null
early_stopping_patience: null
eval_sample_packing: true
eval_table_size: null
evals_per_epoch: 1
flash_attention: false
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 2
gradient_checkpointing: true
group_by_length: false
learning_rate: 3e-5
load_in_4bit: true
load_in_8bit: false
logging_steps: 1
lora_alpha: 16
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_modules_to_save:
- embed_tokens
- lm_head
lora_r: 32
lora_target_linear: true
lr_scheduler: cosine
max_steps: 50
micro_batch_size: 1
model_type: CohereForCausalLM
num_epochs: 1
optimizer: paged_adamw_8bit
output_dir: ./outputs/lora-out
pad_to_sequence_len: true
resume_from_checkpoint: null
sample_packing: true
saves_per_epoch: 1
sdp_attention: true
sequence_len: 2048
special_tokens:
bos_token: <BOS_TOKEN>
eos_token: <|END_OF_TURN_TOKEN|>
unk_token: <PAD>
strict: false
tf32: false
tokens:
- <|START_OF_TURN_TOKEN|>
- <|END_OF_TURN_TOKEN|>
train_on_inputs: false
val_set_size: 0.05
wandb_entity: matrixportalx-none
wandb_log_model: all
wandb_name: aya-turkish-medical
wandb_project: matrixportalx-none
wandb_watch: gradients
warmup_steps: 1
weight_decay: 0.0
xformers_attention: null
```
</details><br>
# outputs/lora-out
This model is a fine-tuned version of [CohereLabs/aya-expanse-8b](https://huggingface.co/CohereLabs/aya-expanse-8b) on the matrixportal/turkish_medical_alpaca dataset.
It achieves the following results on the evaluation set:
- Loss: 6.7830
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 2
- training_steps: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 3.0385 | 0.0172 | 50 | 6.7830 |
### Framework versions
- PEFT 0.15.1
- Transformers 4.51.0
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1 |