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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-3_180-samples_config-1_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_180-samples_config-1_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: 1.4002
## 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: 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: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.6392 | 1.0 | 17 | 1.6279 |
| 1.4618 | 2.0 | 34 | 1.4343 |
| 1.2006 | 3.0 | 51 | 1.2241 |
| 1.0799 | 4.0 | 68 | 1.1761 |
| 1.0615 | 5.0 | 85 | 1.1524 |
| 1.0045 | 6.0 | 102 | 1.1361 |
| 0.9831 | 7.0 | 119 | 1.1392 |
| 0.8698 | 8.0 | 136 | 1.1567 |
| 0.7759 | 9.0 | 153 | 1.1918 |
| 0.7296 | 10.0 | 170 | 1.2537 |
| 0.6747 | 11.0 | 187 | 1.2852 |
| 0.4777 | 12.0 | 204 | 1.3877 |
| 0.5052 | 13.0 | 221 | 1.4002 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |