---
library_name: transformers
license: apache-2.0
base_model: Qwen/Qwen2-1.5B
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fine_tuned_cmv_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_cmv_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: 0.0523
- Accuracy: 0.9931

## 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: 24
- eval_batch_size: 24
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.3459        | 0.1083 | 100  | 0.1297          | 0.9602   |
| 0.1385        | 0.2167 | 200  | 0.0771          | 0.9805   |
| 0.0918        | 0.3250 | 300  | 0.0951          | 0.9825   |
| 0.1103        | 0.4334 | 400  | 0.0834          | 0.9813   |
| 0.0943        | 0.5417 | 500  | 0.0607          | 0.9821   |
| 0.0692        | 0.6501 | 600  | 0.0714          | 0.9866   |
| 0.0584        | 0.7584 | 700  | 0.0607          | 0.9858   |
| 0.0599        | 0.8667 | 800  | 0.0531          | 0.9874   |
| 0.0672        | 0.9751 | 900  | 0.0312          | 0.9915   |
| 0.0086        | 1.0834 | 1000 | 0.0494          | 0.9919   |
| 0.0084        | 1.1918 | 1100 | 0.0621          | 0.9890   |
| 0.0225        | 1.3001 | 1200 | 0.0433          | 0.9927   |
| 0.0146        | 1.4085 | 1300 | 0.0684          | 0.9870   |
| 0.0126        | 1.5168 | 1400 | 0.0960          | 0.9878   |
| 0.0143        | 1.6251 | 1500 | 0.0454          | 0.9927   |
| 0.0081        | 1.7335 | 1600 | 0.0671          | 0.9907   |
| 0.0064        | 1.8418 | 1700 | 0.0526          | 0.9919   |
| 0.0007        | 1.9502 | 1800 | 0.0458          | 0.9931   |
| 0.003         | 2.0585 | 1900 | 0.0523          | 0.9931   |


### Framework versions

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