|
--- |
|
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct |
|
datasets: |
|
- GaetanMichelet/chat-60_ft_task-1 |
|
- GaetanMichelet/chat-120_ft_task-1 |
|
- GaetanMichelet/chat-180_ft_task-1 |
|
library_name: peft |
|
license: llama3.1 |
|
tags: |
|
- alignment-handbook |
|
- trl |
|
- sft |
|
- generated_from_trainer |
|
model-index: |
|
- name: Llama-31-8B_task-1_180-samples_config-4_full |
|
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. --> |
|
|
|
# Llama-31-8B_task-1_180-samples_config-4_full |
|
|
|
This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co./meta-llama/Meta-Llama-3.1-8B-Instruct) on the GaetanMichelet/chat-60_ft_task-1, the GaetanMichelet/chat-120_ft_task-1 and the GaetanMichelet/chat-180_ft_task-1 datasets. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.9048 |
|
|
|
## 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: 1e-05 |
|
- train_batch_size: 1 |
|
- eval_batch_size: 1 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- gradient_accumulation_steps: 16 |
|
- total_train_batch_size: 16 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 150 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-------:|:----:|:---------------:| |
|
| 2.4745 | 0.9412 | 8 | 2.4335 | |
|
| 2.4286 | 2.0 | 17 | 2.4114 | |
|
| 2.419 | 2.9412 | 25 | 2.3814 | |
|
| 2.3475 | 4.0 | 34 | 2.3262 | |
|
| 2.3147 | 4.9412 | 42 | 2.2541 | |
|
| 2.2214 | 6.0 | 51 | 2.1716 | |
|
| 2.1097 | 6.9412 | 59 | 2.0745 | |
|
| 1.9617 | 8.0 | 68 | 1.9479 | |
|
| 1.908 | 8.9412 | 76 | 1.8375 | |
|
| 1.7669 | 10.0 | 85 | 1.6953 | |
|
| 1.6325 | 10.9412 | 93 | 1.5461 | |
|
| 1.3201 | 12.0 | 102 | 1.3739 | |
|
| 1.2477 | 12.9412 | 110 | 1.2331 | |
|
| 1.163 | 14.0 | 119 | 1.1330 | |
|
| 1.0579 | 14.9412 | 127 | 1.0861 | |
|
| 1.0655 | 16.0 | 136 | 1.0611 | |
|
| 0.9976 | 16.9412 | 144 | 1.0455 | |
|
| 1.0285 | 18.0 | 153 | 1.0318 | |
|
| 0.998 | 18.9412 | 161 | 1.0205 | |
|
| 1.0038 | 20.0 | 170 | 1.0102 | |
|
| 0.9907 | 20.9412 | 178 | 1.0020 | |
|
| 0.9673 | 22.0 | 187 | 0.9929 | |
|
| 0.95 | 22.9412 | 195 | 0.9870 | |
|
| 0.9467 | 24.0 | 204 | 0.9801 | |
|
| 0.9423 | 24.9412 | 212 | 0.9737 | |
|
| 0.937 | 26.0 | 221 | 0.9675 | |
|
| 0.9035 | 26.9412 | 229 | 0.9626 | |
|
| 0.9074 | 28.0 | 238 | 0.9582 | |
|
| 0.8944 | 28.9412 | 246 | 0.9534 | |
|
| 0.8785 | 30.0 | 255 | 0.9493 | |
|
| 0.8797 | 30.9412 | 263 | 0.9451 | |
|
| 0.8764 | 32.0 | 272 | 0.9422 | |
|
| 0.8903 | 32.9412 | 280 | 0.9389 | |
|
| 0.8835 | 34.0 | 289 | 0.9377 | |
|
| 0.8452 | 34.9412 | 297 | 0.9332 | |
|
| 0.8777 | 36.0 | 306 | 0.9272 | |
|
| 0.8101 | 36.9412 | 314 | 0.9257 | |
|
| 0.8526 | 38.0 | 323 | 0.9229 | |
|
| 0.8228 | 38.9412 | 331 | 0.9197 | |
|
| 0.8066 | 40.0 | 340 | 0.9176 | |
|
| 0.7701 | 40.9412 | 348 | 0.9199 | |
|
| 0.8132 | 42.0 | 357 | 0.9162 | |
|
| 0.7804 | 42.9412 | 365 | 0.9104 | |
|
| 0.7508 | 44.0 | 374 | 0.9083 | |
|
| 0.7192 | 44.9412 | 382 | 0.9052 | |
|
| 0.7633 | 46.0 | 391 | 0.9048 | |
|
| 0.7534 | 46.9412 | 399 | 0.9052 | |
|
| 0.666 | 48.0 | 408 | 0.9151 | |
|
| 0.7298 | 48.9412 | 416 | 0.9143 | |
|
| 0.6815 | 50.0 | 425 | 0.9157 | |
|
| 0.6845 | 50.9412 | 433 | 0.9170 | |
|
| 0.6524 | 52.0 | 442 | 0.9216 | |
|
| 0.6397 | 52.9412 | 450 | 0.9228 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.12.0 |
|
- Transformers 4.44.0 |
|
- Pytorch 2.1.2+cu121 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
