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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_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
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