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--- |
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library_name: transformers |
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base_model: UWB-AIR/Czert-B-base-cased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: czert_lr2e-05_bs4_train287_max_len256 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# czert_lr2e-05_bs4_train287_max_len256 |
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This model is a fine-tuned version of [UWB-AIR/Czert-B-base-cased](https://huggingface.co/UWB-AIR/Czert-B-base-cased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1677 |
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- Precision: 0.9165 |
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- Recall: 0.9328 |
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- F1: 0.9246 |
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- Accuracy: 0.9561 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 72 | 0.2932 | 0.8413 | 0.8522 | 0.8467 | 0.9163 | |
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| No log | 2.0 | 144 | 0.1967 | 0.8936 | 0.8885 | 0.8910 | 0.9391 | |
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| No log | 3.0 | 216 | 0.1875 | 0.9168 | 0.8885 | 0.9024 | 0.9458 | |
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| No log | 4.0 | 288 | 0.1647 | 0.9079 | 0.9087 | 0.9083 | 0.9504 | |
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| No log | 5.0 | 360 | 0.1658 | 0.9298 | 0.9078 | 0.9186 | 0.9544 | |
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| No log | 6.0 | 432 | 0.1602 | 0.9258 | 0.9276 | 0.9267 | 0.9590 | |
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| 0.1926 | 7.0 | 504 | 0.1642 | 0.9209 | 0.9223 | 0.9216 | 0.9565 | |
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| 0.1926 | 8.0 | 576 | 0.1697 | 0.9298 | 0.9271 | 0.9284 | 0.9602 | |
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| 0.1926 | 9.0 | 648 | 0.1679 | 0.9287 | 0.9247 | 0.9267 | 0.9590 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.3.1 |
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- Tokenizers 0.20.0 |
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