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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_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
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