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---
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
datasets:
- GaetanMichelet/chat-60_ft_task-3
- GaetanMichelet/chat-120_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_120-samples_config-2_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-3_120-samples_config-2_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-3 and the GaetanMichelet/chat-120_ft_task-3 datasets.
It achieves the following results on the evaluation set:
- Loss: 1.1336
## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 1.7269 | 0.9091 | 5 | 1.6901 |
| 1.6699 | 2.0 | 11 | 1.5939 |
| 1.5273 | 2.9091 | 16 | 1.5005 |
| 1.3953 | 4.0 | 22 | 1.3805 |
| 1.2642 | 4.9091 | 27 | 1.2621 |
| 1.1571 | 6.0 | 33 | 1.1986 |
| 1.1345 | 6.9091 | 38 | 1.1788 |
| 1.1145 | 8.0 | 44 | 1.1606 |
| 1.0654 | 8.9091 | 49 | 1.1505 |
| 1.0821 | 10.0 | 55 | 1.1417 |
| 1.0346 | 10.9091 | 60 | 1.1381 |
| 1.0027 | 12.0 | 66 | 1.1336 |
| 0.9693 | 12.9091 | 71 | 1.1350 |
| 0.9594 | 14.0 | 77 | 1.1414 |
| 0.8512 | 14.9091 | 82 | 1.1548 |
| 0.863 | 16.0 | 88 | 1.1607 |
| 0.8028 | 16.9091 | 93 | 1.1746 |
| 0.731 | 18.0 | 99 | 1.2033 |
| 0.7089 | 18.9091 | 104 | 1.2296 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |