---
library_name: transformers
license: apache-2.0
base_model: Qwen/Qwen2-1.5B
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fine_tuned_wp_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_wp_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: 0.0638
- Accuracy: 0.9897

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.6619        | 0.0285 | 100  | 0.9984          | 0.8816   |
| 0.4074        | 0.0570 | 200  | 0.2584          | 0.9194   |
| 0.2873        | 0.0856 | 300  | 0.5169          | 0.9393   |
| 0.1938        | 0.1141 | 400  | 0.1101          | 0.9843   |
| 0.123         | 0.1426 | 500  | 0.0877          | 0.9830   |
| 0.2114        | 0.1711 | 600  | 0.2161          | 0.9599   |
| 0.1381        | 0.1997 | 700  | 0.1234          | 0.9782   |
| 0.1311        | 0.2282 | 800  | 0.4941          | 0.9496   |
| 0.1807        | 0.2567 | 900  | 0.1084          | 0.9730   |
| 0.143         | 0.2852 | 1000 | 0.1180          | 0.9801   |
| 0.0847        | 0.3137 | 1100 | 0.0704          | 0.9849   |
| 0.0757        | 0.3423 | 1200 | 0.0436          | 0.9884   |
| 0.1022        | 0.3708 | 1300 | 0.0757          | 0.9811   |
| 0.1659        | 0.3993 | 1400 | 0.1003          | 0.9823   |
| 0.1926        | 0.4278 | 1500 | 0.0462          | 0.9901   |
| 0.1627        | 0.4564 | 1600 | 0.0925          | 0.9817   |
| 0.1789        | 0.4849 | 1700 | 0.2666          | 0.9599   |
| 0.1518        | 0.5134 | 1800 | 0.0978          | 0.9775   |
| 0.0888        | 0.5419 | 1900 | 0.0871          | 0.9791   |
| 0.1079        | 0.5705 | 2000 | 0.0390          | 0.9920   |
| 0.04          | 0.5990 | 2100 | 0.0571          | 0.9907   |
| 0.0573        | 0.6275 | 2200 | 0.0521          | 0.9878   |
| 0.0633        | 0.6560 | 2300 | 0.0497          | 0.9891   |
| 0.0857        | 0.6845 | 2400 | 0.0575          | 0.9894   |
| 0.1061        | 0.7131 | 2500 | 0.0628          | 0.9894   |
| 0.0575        | 0.7416 | 2600 | 0.0721          | 0.9891   |
| 0.0741        | 0.7701 | 2700 | 0.1140          | 0.9772   |
| 0.0662        | 0.7986 | 2800 | 0.1028          | 0.9804   |
| 0.0585        | 0.8272 | 2900 | 0.0419          | 0.9926   |
| 0.0647        | 0.8557 | 3000 | 0.0638          | 0.9897   |


### Framework versions

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