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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_180-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_180-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 the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2316
## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 2.1079 | 0.9412 | 8 | 2.0439 |
| 1.7735 | 2.0 | 17 | 1.6643 |
| 1.4106 | 2.9412 | 25 | 1.2322 |
| 0.901 | 4.0 | 34 | 0.9259 |
| 0.8657 | 4.9412 | 42 | 0.8770 |
| 0.846 | 6.0 | 51 | 0.8422 |
| 0.7582 | 6.9412 | 59 | 0.8153 |
| 0.7203 | 8.0 | 68 | 0.7906 |
| 0.6598 | 8.9412 | 76 | 0.7848 |
| 0.5979 | 10.0 | 85 | 0.7954 |
| 0.5547 | 10.9412 | 93 | 0.8095 |
| 0.4007 | 12.0 | 102 | 0.8623 |
| 0.3489 | 12.9412 | 110 | 0.9627 |
| 0.2894 | 14.0 | 119 | 1.0531 |
| 0.1972 | 14.9412 | 127 | 1.1217 |
| 0.1682 | 16.0 | 136 | 1.2316 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |