---
library_name: transformers
license: llama3.2
base_model: meta-llama/Llama-3.2-3b-instruct
tags:
- generated_from_trainer
model-index:
- name: llama-cot-o1
  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. -->

# llama-cot-o1

This model is a fine-tuned version of [meta-llama/Llama-3.2-3b-instruct](https://huggingface.co/meta-llama/Llama-3.2-3b-instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6532

## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Use adamw_torch_fused 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.7259        | 0.2168 | 500  | 0.7316          |
| 0.6867        | 0.4336 | 1000 | 0.6930          |
| 0.6642        | 0.6504 | 1500 | 0.6759          |
| 0.6496        | 0.8672 | 2000 | 0.6659          |
| 0.6102        | 1.0837 | 2500 | 0.6615          |
| 0.6107        | 1.3005 | 3000 | 0.6574          |
| 0.6105        | 1.5173 | 3500 | 0.6546          |
| 0.5929        | 1.7341 | 4000 | 0.6529          |
| 0.5987        | 1.9509 | 4500 | 0.6519          |
| 0.5904        | 2.1674 | 5000 | 0.6533          |
| 0.5793        | 2.3842 | 5500 | 0.6532          |
| 0.5826        | 2.6010 | 6000 | 0.6532          |
| 0.5903        | 2.8178 | 6500 | 0.6532          |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1
- Datasets 3.2.0
- Tokenizers 0.21.0