|
--- |
|
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct |
|
datasets: |
|
- GaetanMichelet/chat-60_ft_task-1 |
|
- GaetanMichelet/chat-120_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_120-samples_config-3 |
|
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_120-samples_config-3 |
|
|
|
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 and the GaetanMichelet/chat-120_ft_task-1 datasets. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.2659 |
|
|
|
## 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: 8 |
|
- total_train_batch_size: 8 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 1.9625 | 1.0 | 11 | 2.0994 | |
|
| 2.1365 | 2.0 | 22 | 2.0816 | |
|
| 2.1371 | 3.0 | 33 | 2.0467 | |
|
| 2.0536 | 4.0 | 44 | 1.9862 | |
|
| 1.8317 | 5.0 | 55 | 1.8956 | |
|
| 1.7607 | 6.0 | 66 | 1.7668 | |
|
| 1.6452 | 7.0 | 77 | 1.6453 | |
|
| 1.548 | 8.0 | 88 | 1.5728 | |
|
| 1.4631 | 9.0 | 99 | 1.5217 | |
|
| 1.4126 | 10.0 | 110 | 1.4711 | |
|
| 1.3079 | 11.0 | 121 | 1.4176 | |
|
| 1.3012 | 12.0 | 132 | 1.3769 | |
|
| 1.2575 | 13.0 | 143 | 1.3423 | |
|
| 1.2537 | 14.0 | 154 | 1.3098 | |
|
| 1.1994 | 15.0 | 165 | 1.2874 | |
|
| 1.1054 | 16.0 | 176 | 1.2713 | |
|
| 1.0452 | 17.0 | 187 | 1.2680 | |
|
| 1.0716 | 18.0 | 198 | 1.2659 | |
|
| 0.9207 | 19.0 | 209 | 1.2755 | |
|
| 0.8712 | 20.0 | 220 | 1.2918 | |
|
| 0.8179 | 21.0 | 231 | 1.3371 | |
|
| 0.6485 | 22.0 | 242 | 1.3561 | |
|
| 0.6958 | 23.0 | 253 | 1.4414 | |
|
| 0.5845 | 24.0 | 264 | 1.5147 | |
|
| 0.5274 | 25.0 | 275 | 1.5912 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.12.0 |
|
- Transformers 4.44.0 |
|
- Pytorch 2.1.2+cu121 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
