---
library_name: transformers
license: llama3.2
base_model: meta-llama/Llama-3.2-3B
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
- trl
- sft
- generated_from_trainer
datasets:
- EEG123/DE_subject_2
model-index:
- name: subject2-test1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# subject2-test1

This model is a fine-tuned version of [meta-llama/Llama-3.2-3B](https://huggingface.co/meta-llama/Llama-3.2-3B) on the EEG123/DE_subject_2 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0319

## 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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.3241        | 1.0   | 377  | 0.5891          |
| 0.0017        | 2.0   | 754  | 1.2835          |
| 0.0009        | 3.0   | 1131 | 1.0319          |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1