---
library_name: transformers
license: llama3.2
base_model: meta-llama/Llama-3.2-1B
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [meta-llama/Llama-3.2-1B](https://huggingface.co/meta-llama/Llama-3.2-1B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1652
- Accuracy: 0.0431

## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 2.6185        | 0.9970 | 82   | 2.6059          | 0.0323   |
| 2.4398        | 1.9939 | 164  | 2.6266          | 0.0582   |
| 2.4161        | 2.9909 | 246  | 2.3381          | 0.0905   |
| 2.3511        | 4.0    | 329  | 2.2989          | 0.1013   |
| 2.2733        | 4.9970 | 411  | 2.2880          | 0.0323   |
| 2.3463        | 5.9939 | 493  | 2.1652          | 0.0431   |
| 2.253         | 6.9909 | 575  | 2.1971          | 0.0431   |
| 2.2243        | 7.9757 | 656  | 2.1854          | 0.1272   |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3