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---
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
datasets:
- GaetanMichelet/chat-60_ft_task-1
- GaetanMichelet/chat-120_ft_task-1
- GaetanMichelet/chat-180_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_180-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_180-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, the GaetanMichelet/chat-120_ft_task-1 and the GaetanMichelet/chat-180_ft_task-1 datasets.
It achieves the following results on the evaluation set:
- Loss: 0.9048
## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 2.4745 | 0.9412 | 8 | 2.4335 |
| 2.4286 | 2.0 | 17 | 2.4114 |
| 2.419 | 2.9412 | 25 | 2.3814 |
| 2.3475 | 4.0 | 34 | 2.3262 |
| 2.3147 | 4.9412 | 42 | 2.2541 |
| 2.2214 | 6.0 | 51 | 2.1716 |
| 2.1097 | 6.9412 | 59 | 2.0745 |
| 1.9617 | 8.0 | 68 | 1.9479 |
| 1.908 | 8.9412 | 76 | 1.8375 |
| 1.7669 | 10.0 | 85 | 1.6953 |
| 1.6325 | 10.9412 | 93 | 1.5461 |
| 1.3201 | 12.0 | 102 | 1.3739 |
| 1.2477 | 12.9412 | 110 | 1.2331 |
| 1.163 | 14.0 | 119 | 1.1330 |
| 1.0579 | 14.9412 | 127 | 1.0861 |
| 1.0655 | 16.0 | 136 | 1.0611 |
| 0.9976 | 16.9412 | 144 | 1.0455 |
| 1.0285 | 18.0 | 153 | 1.0318 |
| 0.998 | 18.9412 | 161 | 1.0205 |
| 1.0038 | 20.0 | 170 | 1.0102 |
| 0.9907 | 20.9412 | 178 | 1.0020 |
| 0.9673 | 22.0 | 187 | 0.9929 |
| 0.95 | 22.9412 | 195 | 0.9870 |
| 0.9467 | 24.0 | 204 | 0.9801 |
| 0.9423 | 24.9412 | 212 | 0.9737 |
| 0.937 | 26.0 | 221 | 0.9675 |
| 0.9035 | 26.9412 | 229 | 0.9626 |
| 0.9074 | 28.0 | 238 | 0.9582 |
| 0.8944 | 28.9412 | 246 | 0.9534 |
| 0.8785 | 30.0 | 255 | 0.9493 |
| 0.8797 | 30.9412 | 263 | 0.9451 |
| 0.8764 | 32.0 | 272 | 0.9422 |
| 0.8903 | 32.9412 | 280 | 0.9389 |
| 0.8835 | 34.0 | 289 | 0.9377 |
| 0.8452 | 34.9412 | 297 | 0.9332 |
| 0.8777 | 36.0 | 306 | 0.9272 |
| 0.8101 | 36.9412 | 314 | 0.9257 |
| 0.8526 | 38.0 | 323 | 0.9229 |
| 0.8228 | 38.9412 | 331 | 0.9197 |
| 0.8066 | 40.0 | 340 | 0.9176 |
| 0.7701 | 40.9412 | 348 | 0.9199 |
| 0.8132 | 42.0 | 357 | 0.9162 |
| 0.7804 | 42.9412 | 365 | 0.9104 |
| 0.7508 | 44.0 | 374 | 0.9083 |
| 0.7192 | 44.9412 | 382 | 0.9052 |
| 0.7633 | 46.0 | 391 | 0.9048 |
| 0.7534 | 46.9412 | 399 | 0.9052 |
| 0.666 | 48.0 | 408 | 0.9151 |
| 0.7298 | 48.9412 | 416 | 0.9143 |
| 0.6815 | 50.0 | 425 | 0.9157 |
| 0.6845 | 50.9412 | 433 | 0.9170 |
| 0.6524 | 52.0 | 442 | 0.9216 |
| 0.6397 | 52.9412 | 450 | 0.9228 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |