---
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-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_120-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 and the GaetanMichelet/chat-120_ft_task-1 datasets.
It achieves the following results on the evaluation set:
- Loss: 0.9042

## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 2.4687        | 0.9091  | 5    | 2.4589          |
| 2.5083        | 2.0     | 11   | 2.4440          |
| 2.4676        | 2.9091  | 16   | 2.4218          |
| 2.4562        | 4.0     | 22   | 2.3870          |
| 2.377         | 4.9091  | 27   | 2.3475          |
| 2.3303        | 6.0     | 33   | 2.2793          |
| 2.2553        | 6.9091  | 38   | 2.2254          |
| 2.174         | 8.0     | 44   | 2.1392          |
| 2.131         | 8.9091  | 49   | 2.0661          |
| 2.0142        | 10.0    | 55   | 1.9626          |
| 1.8873        | 10.9091 | 60   | 1.8746          |
| 1.7633        | 12.0    | 66   | 1.7650          |
| 1.726         | 12.9091 | 71   | 1.6563          |
| 1.5711        | 14.0    | 77   | 1.5123          |
| 1.4344        | 14.9091 | 82   | 1.3950          |
| 1.3201        | 16.0    | 88   | 1.2661          |
| 1.1787        | 16.9091 | 93   | 1.1831          |
| 1.1444        | 18.0    | 99   | 1.1188          |
| 1.0591        | 18.9091 | 104  | 1.0836          |
| 1.0151        | 20.0    | 110  | 1.0540          |
| 1.0277        | 20.9091 | 115  | 1.0388          |
| 1.0025        | 22.0    | 121  | 1.0250          |
| 1.0161        | 22.9091 | 126  | 1.0154          |
| 0.9946        | 24.0    | 132  | 1.0047          |
| 0.9773        | 24.9091 | 137  | 0.9970          |
| 0.9708        | 26.0    | 143  | 0.9890          |
| 0.9374        | 26.9091 | 148  | 0.9822          |
| 0.9403        | 28.0    | 154  | 0.9751          |
| 0.94          | 28.9091 | 159  | 0.9703          |
| 0.902         | 30.0    | 165  | 0.9633          |
| 0.9215        | 30.9091 | 170  | 0.9604          |
| 0.8854        | 32.0    | 176  | 0.9548          |
| 0.96          | 32.9091 | 181  | 0.9503          |
| 0.9162        | 34.0    | 187  | 0.9453          |
| 0.8686        | 34.9091 | 192  | 0.9429          |
| 0.906         | 36.0    | 198  | 0.9385          |
| 0.8762        | 36.9091 | 203  | 0.9354          |
| 0.8929        | 38.0    | 209  | 0.9332          |
| 0.8687        | 38.9091 | 214  | 0.9301          |
| 0.8933        | 40.0    | 220  | 0.9279          |
| 0.858         | 40.9091 | 225  | 0.9241          |
| 0.8481        | 42.0    | 231  | 0.9223          |
| 0.8228        | 42.9091 | 236  | 0.9217          |
| 0.8593        | 44.0    | 242  | 0.9186          |
| 0.8238        | 44.9091 | 247  | 0.9156          |
| 0.8081        | 46.0    | 253  | 0.9161          |
| 0.8327        | 46.9091 | 258  | 0.9129          |
| 0.8029        | 48.0    | 264  | 0.9110          |
| 0.7909        | 48.9091 | 269  | 0.9094          |
| 0.7826        | 50.0    | 275  | 0.9079          |
| 0.773         | 50.9091 | 280  | 0.9122          |
| 0.7377        | 52.0    | 286  | 0.9078          |
| 0.7491        | 52.9091 | 291  | 0.9050          |
| 0.7414        | 54.0    | 297  | 0.9093          |
| 0.7275        | 54.9091 | 302  | 0.9053          |
| 0.7198        | 56.0    | 308  | 0.9046          |
| 0.7203        | 56.9091 | 313  | 0.9093          |
| 0.6903        | 58.0    | 319  | 0.9042          |
| 0.6987        | 58.9091 | 324  | 0.9107          |
| 0.7141        | 60.0    | 330  | 0.9079          |
| 0.7023        | 60.9091 | 335  | 0.9120          |
| 0.6945        | 62.0    | 341  | 0.9087          |
| 0.6897        | 62.9091 | 346  | 0.9130          |
| 0.6597        | 64.0    | 352  | 0.9134          |
| 0.6954        | 64.9091 | 357  | 0.9120          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1