---
library_name: transformers
license: apache-2.0
base_model: Qwen/Qwen2-1.5B
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fine_tuned_hswag_callback10
  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. -->

# fine_tuned_hswag_callback10

This model is a fine-tuned version of [Qwen/Qwen2-1.5B](https://huggingface.co/Qwen/Qwen2-1.5B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1861
- Accuracy: 0.9602

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.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: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.7551        | 0.0322 | 100  | 0.4489          | 0.9012   |
| 0.3977        | 0.0644 | 200  | 0.5959          | 0.8943   |
| 0.3608        | 0.0966 | 300  | 0.2267          | 0.9258   |
| 0.3092        | 0.1287 | 400  | 0.1801          | 0.9374   |
| 0.1932        | 0.1609 | 500  | 0.1921          | 0.9562   |
| 0.1405        | 0.1931 | 600  | 0.2487          | 0.9573   |
| 0.3093        | 0.2253 | 700  | 0.1245          | 0.9573   |
| 0.1804        | 0.2575 | 800  | 0.1496          | 0.9602   |
| 0.1717        | 0.2897 | 900  | 0.1923          | 0.9573   |
| 0.1986        | 0.3219 | 1000 | 0.4235          | 0.9167   |
| 0.1786        | 0.3540 | 1100 | 0.1436          | 0.9591   |
| 0.1563        | 0.3862 | 1200 | 0.2635          | 0.9468   |
| 0.188         | 0.4184 | 1300 | 0.1891          | 0.9540   |
| 0.137         | 0.4506 | 1400 | 0.2017          | 0.9348   |
| 0.1438        | 0.4828 | 1500 | 0.1510          | 0.9660   |
| 0.1241        | 0.5150 | 1600 | 0.2152          | 0.9551   |
| 0.1793        | 0.5472 | 1700 | 0.1861          | 0.9602   |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0+cu126
- Datasets 3.3.2
- Tokenizers 0.21.0