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---
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
datasets:
- GaetanMichelet/chat-60_ft_task-1_auto
library_name: peft
license: llama3.1
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: Llama-31-8B_task-1_60-samples_config-2_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-1_60-samples_config-2_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-1_auto dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9200
## 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: 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: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 1.1077 | 0.6957 | 2 | 1.2225 |
| 1.1089 | 1.7391 | 5 | 1.1334 |
| 0.954 | 2.7826 | 8 | 1.0066 |
| 0.9473 | 3.8261 | 11 | 0.9689 |
| 0.7929 | 4.8696 | 14 | 0.9281 |
| 0.7943 | 5.9130 | 17 | 0.9352 |
| 0.6696 | 6.9565 | 20 | 0.9296 |
| 0.5976 | 8.0 | 23 | 0.9200 |
| 0.5767 | 8.6957 | 25 | 0.9291 |
| 0.4423 | 9.7391 | 28 | 0.9620 |
| 0.4059 | 10.7826 | 31 | 1.0431 |
| 0.2734 | 11.8261 | 34 | 1.1927 |
| 0.2387 | 12.8696 | 37 | 1.3013 |
| 0.1347 | 13.9130 | 40 | 1.4096 |
| 0.0897 | 14.9565 | 43 | 1.5471 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |