---
base_model: meta-llama/Llama-3.1-8B-Instruct
library_name: peft
license: llama3.1
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: Llama-3.1-8B-Instruct-sft-1000
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Llama-3.1-8B-Instruct-sft-1000

This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on the bct_non_cot_sft_1000 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0757

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.074         | 1.7778 | 50   | 0.0757          |
| 0.0309        | 3.5556 | 100  | 0.0856          |
| 0.012         | 5.3333 | 150  | 0.1149          |
| 0.0034        | 7.1111 | 200  | 0.1489          |
| 0.0024        | 8.8889 | 250  | 0.1494          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.45.2
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.20.0