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---
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
datasets:
- GaetanMichelet/chat-60_ft_task-2
- GaetanMichelet/chat-120_ft_task-2
library_name: peft
license: llama3.1
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: Llama-31-8B_task-2_120-samples_config-4
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-2_120-samples_config-4
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-2 and the GaetanMichelet/chat-120_ft_task-2 datasets.
It achieves the following results on the evaluation set:
- Loss: 0.7144
## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 1.1544 | 0.9091 | 5 | 1.1237 |
| 1.132 | 2.0 | 11 | 1.1193 |
| 1.0689 | 2.9091 | 16 | 1.1136 |
| 1.0956 | 4.0 | 22 | 1.1011 |
| 1.1157 | 4.9091 | 27 | 1.0871 |
| 1.0778 | 6.0 | 33 | 1.0639 |
| 1.0458 | 6.9091 | 38 | 1.0393 |
| 0.9854 | 8.0 | 44 | 1.0027 |
| 0.9996 | 8.9091 | 49 | 0.9696 |
| 0.8991 | 10.0 | 55 | 0.9317 |
| 0.8897 | 10.9091 | 60 | 0.9052 |
| 0.8711 | 12.0 | 66 | 0.8788 |
| 0.8809 | 12.9091 | 71 | 0.8588 |
| 0.7972 | 14.0 | 77 | 0.8368 |
| 0.8156 | 14.9091 | 82 | 0.8208 |
| 0.7815 | 16.0 | 88 | 0.8057 |
| 0.7492 | 16.9091 | 93 | 0.7956 |
| 0.7587 | 18.0 | 99 | 0.7855 |
| 0.7483 | 18.9091 | 104 | 0.7780 |
| 0.7296 | 20.0 | 110 | 0.7695 |
| 0.7441 | 20.9091 | 115 | 0.7629 |
| 0.7176 | 22.0 | 121 | 0.7561 |
| 0.7033 | 22.9091 | 126 | 0.7508 |
| 0.6906 | 24.0 | 132 | 0.7443 |
| 0.6954 | 24.9091 | 137 | 0.7396 |
| 0.6578 | 26.0 | 143 | 0.7344 |
| 0.6495 | 26.9091 | 148 | 0.7310 |
| 0.6391 | 28.0 | 154 | 0.7269 |
| 0.6442 | 28.9091 | 159 | 0.7237 |
| 0.6268 | 30.0 | 165 | 0.7199 |
| 0.6536 | 30.9091 | 170 | 0.7183 |
| 0.6092 | 32.0 | 176 | 0.7163 |
| 0.621 | 32.9091 | 181 | 0.7149 |
| 0.5823 | 34.0 | 187 | 0.7144 |
| 0.5651 | 34.9091 | 192 | 0.7156 |
| 0.5951 | 36.0 | 198 | 0.7164 |
| 0.5637 | 36.9091 | 203 | 0.7195 |
| 0.5669 | 38.0 | 209 | 0.7219 |
| 0.5613 | 38.9091 | 214 | 0.7278 |
| 0.5156 | 40.0 | 220 | 0.7309 |
| 0.5044 | 40.9091 | 225 | 0.7395 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |