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---
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
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