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--- |
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license: cc-by-nc-sa-4.0 |
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base_model: ufal/robeczech-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- cnec |
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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: CNEC_2_0_ext_robeczech-base |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: cnec |
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type: cnec |
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config: default |
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split: validation |
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args: default |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.8633093525179856 |
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- name: Recall |
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type: recall |
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value: 0.8933002481389578 |
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- name: F1 |
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type: f1 |
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value: 0.8780487804878048 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9703429462197973 |
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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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# CNEC_2_0_ext_robeczech-base |
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This model is a fine-tuned version of [ufal/robeczech-base](https://huggingface.co/ufal/robeczech-base) on the cnec dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1663 |
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- Precision: 0.8633 |
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- Recall: 0.8933 |
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- F1: 0.8780 |
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- Accuracy: 0.9703 |
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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: 32 |
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- eval_batch_size: 32 |
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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: 50 |
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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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| 0.2593 | 4.46 | 1000 | 0.1653 | 0.8195 | 0.8223 | 0.8209 | 0.9593 | |
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| 0.1209 | 8.93 | 2000 | 0.1355 | 0.8441 | 0.8789 | 0.8612 | 0.9679 | |
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| 0.0763 | 13.39 | 3000 | 0.1310 | 0.8591 | 0.8893 | 0.8739 | 0.9709 | |
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| 0.0539 | 17.86 | 4000 | 0.1383 | 0.8656 | 0.8953 | 0.8802 | 0.9719 | |
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| 0.0403 | 22.32 | 5000 | 0.1392 | 0.8626 | 0.8943 | 0.8782 | 0.9710 | |
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| 0.0316 | 26.79 | 6000 | 0.1539 | 0.8606 | 0.8948 | 0.8774 | 0.9712 | |
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| 0.0254 | 31.25 | 7000 | 0.1552 | 0.8660 | 0.8913 | 0.8785 | 0.9706 | |
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| 0.0211 | 35.71 | 8000 | 0.1621 | 0.8658 | 0.8968 | 0.8810 | 0.9701 | |
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| 0.0183 | 40.18 | 9000 | 0.1593 | 0.8688 | 0.8973 | 0.8828 | 0.9718 | |
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| 0.0161 | 44.64 | 10000 | 0.1638 | 0.8653 | 0.8993 | 0.8820 | 0.9714 | |
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| 0.015 | 49.11 | 11000 | 0.1663 | 0.8633 | 0.8933 | 0.8780 | 0.9703 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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