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--- |
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license: cc-by-4.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: CTEBMSP_ner_test |
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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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# CTEBMSP_ner_test |
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This model is a fine-tuned version of [chizhikchi/Spanish_disease_finder](https://huggingface.co/chizhikchi/Spanish_disease_finder) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0560 |
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- Diso Precision: 0.8925 |
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- Diso Recall: 0.8945 |
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- Diso F1: 0.8935 |
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- Diso Number: 2645 |
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- Overall Precision: 0.8925 |
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- Overall Recall: 0.8945 |
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- Overall F1: 0.8935 |
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- Overall Accuracy: 0.9899 |
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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: 4e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Diso Precision | Diso Recall | Diso F1 | Diso Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------:|:-----------:|:-------:|:-----------:|:-----------------:|:--------------:|:----------:|:----------------:| |
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| 0.04 | 1.0 | 1570 | 0.0439 | 0.8410 | 0.8858 | 0.8628 | 2645 | 0.8410 | 0.8858 | 0.8628 | 0.9877 | |
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| 0.0173 | 2.0 | 3140 | 0.0487 | 0.8728 | 0.8843 | 0.8785 | 2645 | 0.8728 | 0.8843 | 0.8785 | 0.9885 | |
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| 0.0071 | 3.0 | 4710 | 0.0496 | 0.8911 | 0.8945 | 0.8928 | 2645 | 0.8911 | 0.8945 | 0.8928 | 0.9898 | |
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| 0.0025 | 4.0 | 6280 | 0.0560 | 0.8925 | 0.8945 | 0.8935 | 2645 | 0.8925 | 0.8945 | 0.8935 | 0.9899 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.0+cu116 |
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- Datasets 2.8.0 |
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- Tokenizers 0.13.2 |
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