---
library_name: transformers
license: apache-2.0
base_model: Qwen/Qwen2-1.5B
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fine_tuned_squad_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_squad_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: 0.1183
- Accuracy: 0.9656

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.8142        | 0.0249 | 100  | 0.3328          | 0.8705   |
| 0.4483        | 0.0497 | 200  | 0.2505          | 0.9276   |
| 0.3808        | 0.0746 | 300  | 0.2715          | 0.9267   |
| 0.2638        | 0.0994 | 400  | 0.3570          | 0.9116   |
| 0.3363        | 0.1243 | 500  | 0.3385          | 0.9284   |
| 0.2347        | 0.1491 | 600  | 0.3153          | 0.9273   |
| 0.2882        | 0.1740 | 700  | 0.1504          | 0.9516   |
| 0.1782        | 0.1989 | 800  | 0.1403          | 0.9611   |
| 0.2897        | 0.2237 | 900  | 0.3369          | 0.9424   |
| 0.276         | 0.2486 | 1000 | 0.1714          | 0.9595   |
| 0.1409        | 0.2734 | 1100 | 0.1756          | 0.9527   |
| 0.1726        | 0.2983 | 1200 | 0.1371          | 0.9664   |
| 0.2029        | 0.3231 | 1300 | 0.3187          | 0.9223   |
| 0.1869        | 0.3480 | 1400 | 0.1917          | 0.9561   |
| 0.2551        | 0.3729 | 1500 | 0.1410          | 0.9592   |
| 0.1249        | 0.3977 | 1600 | 0.2447          | 0.9547   |
| 0.1784        | 0.4226 | 1700 | 0.1548          | 0.9687   |
| 0.1567        | 0.4474 | 1800 | 0.2113          | 0.9625   |
| 0.1863        | 0.4723 | 1900 | 0.1238          | 0.9723   |
| 0.2032        | 0.4971 | 2000 | 0.2280          | 0.9516   |
| 0.161         | 0.5220 | 2100 | 0.1819          | 0.9536   |
| 0.1687        | 0.5469 | 2200 | 0.1034          | 0.9757   |
| 0.1196        | 0.5717 | 2300 | 0.0857          | 0.9807   |
| 0.1407        | 0.5966 | 2400 | 0.0824          | 0.9827   |
| 0.1028        | 0.6214 | 2500 | 0.1338          | 0.9757   |
| 0.1257        | 0.6463 | 2600 | 0.0872          | 0.9776   |
| 0.1226        | 0.6711 | 2700 | 0.1050          | 0.9799   |
| 0.1249        | 0.6960 | 2800 | 0.0902          | 0.9776   |
| 0.0763        | 0.7209 | 2900 | 0.1054          | 0.9787   |
| 0.125         | 0.7457 | 3000 | 0.1131          | 0.9765   |
| 0.1257        | 0.7706 | 3100 | 0.2562          | 0.9547   |
| 0.163         | 0.7954 | 3200 | 0.1519          | 0.9746   |
| 0.1246        | 0.8203 | 3300 | 0.1513          | 0.9729   |
| 0.1358        | 0.8451 | 3400 | 0.1183          | 0.9656   |


### Framework versions

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