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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_60-samples_config-2_full_auto
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_60-samples_config-2_full_auto
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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9046
## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 2.2096 | 0.6957 | 2 | 2.1129 |
| 2.167 | 1.7391 | 5 | 1.9558 |
| 1.8726 | 2.7826 | 8 | 1.7428 |
| 1.7678 | 3.8261 | 11 | 1.5017 |
| 1.3895 | 4.8696 | 14 | 1.2525 |
| 1.234 | 5.9130 | 17 | 1.0325 |
| 0.9378 | 6.9565 | 20 | 0.9271 |
| 0.8782 | 8.0 | 23 | 0.8920 |
| 0.8394 | 8.6957 | 25 | 0.8784 |
| 0.7845 | 9.7391 | 28 | 0.8647 |
| 0.7863 | 10.7826 | 31 | 0.8503 |
| 0.7261 | 11.8261 | 34 | 0.8417 |
| 0.7333 | 12.8696 | 37 | 0.8337 |
| 0.6709 | 13.9130 | 40 | 0.8289 |
| 0.6612 | 14.9565 | 43 | 0.8270 |
| 0.6253 | 16.0 | 46 | 0.8289 |
| 0.6012 | 16.6957 | 48 | 0.8323 |
| 0.5792 | 17.7391 | 51 | 0.8385 |
| 0.5162 | 18.7826 | 54 | 0.8561 |
| 0.5219 | 19.8261 | 57 | 0.8603 |
| 0.445 | 20.8696 | 60 | 0.8802 |
| 0.4396 | 21.9130 | 63 | 0.9046 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |