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---
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
datasets:
- GaetanMichelet/chat-60_ft_task-3_auto
- GaetanMichelet/chat-120_ft_task-3_auto
library_name: peft
license: llama3.1
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: Llama-31-8B_task-3_120-samples_config-1_full_auto
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_120-samples_config-1_full_auto
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_auto and the GaetanMichelet/chat-120_ft_task-3_auto datasets.
It achieves the following results on the evaluation set:
- Loss: 1.1182
## 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: 0.0001
- 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: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.6493 | 1.0 | 11 | 1.6402 |
| 1.4499 | 2.0 | 22 | 1.4987 |
| 1.3516 | 3.0 | 33 | 1.3295 |
| 1.2309 | 4.0 | 44 | 1.1897 |
| 1.151 | 5.0 | 55 | 1.1514 |
| 1.1003 | 6.0 | 66 | 1.1307 |
| 1.0537 | 7.0 | 77 | 1.1200 |
| 1.0287 | 8.0 | 88 | 1.1182 |
| 0.9295 | 9.0 | 99 | 1.1300 |
| 0.8133 | 10.0 | 110 | 1.1687 |
| 0.8071 | 11.0 | 121 | 1.2087 |
| 0.6155 | 12.0 | 132 | 1.2670 |
| 0.6191 | 13.0 | 143 | 1.2891 |
| 0.3871 | 14.0 | 154 | 1.4231 |
| 0.2973 | 15.0 | 165 | 1.3964 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |