---
library_name: transformers
license: llama3.2
base_model: meta-llama/Llama-3.2-1B
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: mcmaster-llama3-1b-full-pt
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# mcmaster-llama3-1b-full-pt

This model is a fine-tuned version of [meta-llama/Llama-3.2-1B](https://huggingface.co/meta-llama/Llama-3.2-1B) on the mcmaster dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0319

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Use adamw_torch 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: 5.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.3821        | 0.7436 | 500  | 0.3760          |
| 0.1018        | 1.4876 | 1000 | 0.1019          |
| 0.0376        | 2.2316 | 1500 | 0.0510          |
| 0.0267        | 2.9753 | 2000 | 0.0338          |
| 0.0118        | 3.7193 | 2500 | 0.0310          |
| 0.0055        | 4.4633 | 3000 | 0.0320          |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.5.1
- Datasets 3.1.0
- Tokenizers 0.20.3