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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_1_1_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: 0.8354960234407702 |
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- name: Recall |
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type: recall |
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value: 0.8812362030905078 |
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- name: F1 |
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type: f1 |
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value: 0.8577567683712936 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9450064850843061 |
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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_1_1_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: 0.2816 |
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- Precision: 0.8355 |
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- Recall: 0.8812 |
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- F1: 0.8578 |
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- Accuracy: 0.9450 |
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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: 80 |
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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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| 0.7852 | 10.2 | 1500 | 0.6287 | 0.3577 | 0.2375 | 0.2855 | 0.8413 | |
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| 0.3806 | 20.41 | 3000 | 0.3455 | 0.7275 | 0.7779 | 0.7519 | 0.9240 | |
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| 0.2384 | 30.61 | 4500 | 0.2764 | 0.8139 | 0.8552 | 0.8340 | 0.9383 | |
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| 0.1722 | 40.82 | 6000 | 0.2640 | 0.8361 | 0.8693 | 0.8524 | 0.9450 | |
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| 0.1357 | 51.02 | 7500 | 0.2666 | 0.8362 | 0.8702 | 0.8529 | 0.9454 | |
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| 0.1115 | 61.22 | 9000 | 0.2697 | 0.8423 | 0.8751 | 0.8584 | 0.9457 | |
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| 0.098 | 71.43 | 10500 | 0.2816 | 0.8355 | 0.8812 | 0.8578 | 0.9450 | |
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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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