|
--- |
|
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct |
|
datasets: |
|
- GaetanMichelet/chat-60_ft_task-3 |
|
- GaetanMichelet/chat-120_ft_task-3 |
|
- GaetanMichelet/chat-180_ft_task-3 |
|
library_name: peft |
|
license: llama3.1 |
|
tags: |
|
- alignment-handbook |
|
- trl |
|
- sft |
|
- generated_from_trainer |
|
model-index: |
|
- name: Llama-31-8B_task-3_180-samples_config-4 |
|
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-3_180-samples_config-4 |
|
|
|
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-3, the GaetanMichelet/chat-120_ft_task-3 and the GaetanMichelet/chat-180_ft_task-3 datasets. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4942 |
|
|
|
## 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 | |
|
|:-------------:|:-------:|:----:|:---------------:| |
|
| 2.5495 | 0.9412 | 8 | 2.5077 | |
|
| 2.3733 | 2.0 | 17 | 2.4775 | |
|
| 2.46 | 2.9412 | 25 | 2.4218 | |
|
| 2.4585 | 4.0 | 34 | 2.3278 | |
|
| 2.2624 | 4.9412 | 42 | 2.1919 | |
|
| 2.0553 | 6.0 | 51 | 1.9704 | |
|
| 1.7403 | 6.9412 | 59 | 1.7066 | |
|
| 1.3756 | 8.0 | 68 | 1.3617 | |
|
| 1.11 | 8.9412 | 76 | 1.0613 | |
|
| 0.7161 | 10.0 | 85 | 0.7772 | |
|
| 0.7609 | 10.9412 | 93 | 0.6787 | |
|
| 0.4358 | 12.0 | 102 | 0.6182 | |
|
| 0.4774 | 12.9412 | 110 | 0.5912 | |
|
| 0.5569 | 14.0 | 119 | 0.5746 | |
|
| 0.427 | 14.9412 | 127 | 0.5487 | |
|
| 0.4672 | 16.0 | 136 | 0.5339 | |
|
| 0.3495 | 16.9412 | 144 | 0.5525 | |
|
| 0.4731 | 18.0 | 153 | 0.5323 | |
|
| 0.3913 | 18.9412 | 161 | 0.5243 | |
|
| 0.5624 | 20.0 | 170 | 0.5253 | |
|
| 0.4684 | 20.9412 | 178 | 0.5222 | |
|
| 0.3029 | 22.0 | 187 | 0.5100 | |
|
| 0.3522 | 22.9412 | 195 | 0.5085 | |
|
| 0.3855 | 24.0 | 204 | 0.4971 | |
|
| 0.317 | 24.9412 | 212 | 0.5049 | |
|
| 0.338 | 26.0 | 221 | 0.5016 | |
|
| 0.391 | 26.9412 | 229 | 0.4942 | |
|
| 0.3964 | 28.0 | 238 | 0.5010 | |
|
| 0.2951 | 28.9412 | 246 | 0.5098 | |
|
| 0.4021 | 30.0 | 255 | 0.5068 | |
|
| 0.4021 | 30.9412 | 263 | 0.5070 | |
|
| 0.3456 | 32.0 | 272 | 0.5025 | |
|
| 0.4431 | 32.9412 | 280 | 0.5050 | |
|
| 0.4131 | 34.0 | 289 | 0.5094 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.12.0 |
|
- Transformers 4.44.0 |
|
- Pytorch 2.1.2+cu121 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
