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---
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
library_name: peft
license: llama3.1
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Llama-31-8B_task-1_120-samples_config-3_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_120-samples_config-3_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 None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9369
## 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: 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: 150
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.4681 | 1.0 | 11 | 2.4539 |
| 2.3894 | 2.0 | 22 | 2.4260 |
| 2.4746 | 3.0 | 33 | 2.3827 |
| 2.4177 | 4.0 | 44 | 2.3138 |
| 2.1959 | 5.0 | 55 | 2.2269 |
| 2.16 | 6.0 | 66 | 2.1177 |
| 2.0388 | 7.0 | 77 | 1.9844 |
| 1.8932 | 8.0 | 88 | 1.8442 |
| 1.7199 | 9.0 | 99 | 1.6830 |
| 1.4973 | 10.0 | 110 | 1.4929 |
| 1.2726 | 11.0 | 121 | 1.2980 |
| 1.204 | 12.0 | 132 | 1.1554 |
| 1.0597 | 13.0 | 143 | 1.0772 |
| 1.0642 | 14.0 | 154 | 1.0425 |
| 1.0466 | 15.0 | 165 | 1.0201 |
| 1.0044 | 16.0 | 176 | 1.0010 |
| 0.9967 | 17.0 | 187 | 0.9866 |
| 0.9863 | 18.0 | 198 | 0.9736 |
| 0.9065 | 19.0 | 209 | 0.9644 |
| 0.8669 | 20.0 | 220 | 0.9539 |
| 0.9253 | 21.0 | 231 | 0.9454 |
| 0.872 | 22.0 | 242 | 0.9398 |
| 0.8824 | 23.0 | 253 | 0.9328 |
| 0.8582 | 24.0 | 264 | 0.9283 |
| 0.8763 | 25.0 | 275 | 0.9221 |
| 0.8199 | 26.0 | 286 | 0.9177 |
| 0.7986 | 27.0 | 297 | 0.9146 |
| 0.7754 | 28.0 | 308 | 0.9142 |
| 0.7893 | 29.0 | 319 | 0.9086 |
| 0.7312 | 30.0 | 330 | 0.9087 |
| 0.7431 | 31.0 | 341 | 0.9050 |
| 0.7103 | 32.0 | 352 | 0.9037 |
| 0.6967 | 33.0 | 363 | 0.9092 |
| 0.6502 | 34.0 | 374 | 0.9071 |
| 0.6659 | 35.0 | 385 | 0.9019 |
| 0.7003 | 36.0 | 396 | 0.9015 |
| 0.629 | 37.0 | 407 | 0.9018 |
| 0.6299 | 38.0 | 418 | 0.9081 |
| 0.6259 | 39.0 | 429 | 0.9162 |
| 0.6262 | 40.0 | 440 | 0.9212 |
| 0.5707 | 41.0 | 451 | 0.9212 |
| 0.5749 | 42.0 | 462 | 0.9274 |
| 0.533 | 43.0 | 473 | 0.9369 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |