---
library_name: peft
license: llama3.2
base_model: meta-llama/Llama-3.2-3B
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: meta-llama-Llama-3.2-3B-DottedWSD
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# meta-llama-Llama-3.2-3B-DottedWSD

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 None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1419
- Accuracy: 0.9563

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 512
- optimizer: Use adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.1395        | 0.9997 | 770  | 0.1257          | 0.9473   |
| 0.0797        | 1.9994 | 1540 | 0.1142          | 0.9552   |
| 0.0336        | 2.9991 | 2310 | 0.1419          | 0.9563   |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1