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--- |
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language: |
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- vi |
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license: mit |
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base_model: FacebookAI/xlm-roberta-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: xlm-roberta-base_covid_ner_full |
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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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# xlm-roberta-base_covid_ner_full |
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This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the covid19_ner dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0873 |
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- Patient Id: 0.9883 |
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- Name: 0.9446 |
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- Gender: 0.9785 |
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- Age: 0.9765 |
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- Job: 0.7063 |
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- Location: 0.9538 |
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- Organization: 0.8807 |
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- Date: 0.9851 |
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- Symptom And Disease: 0.8886 |
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- Transportation: 1.0 |
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- F1 Macro: 0.9302 |
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- F1 Micro: 0.9499 |
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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: 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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Patient Id | Name | Gender | Age | Job | Location | Organization | Date | Symptom And Disease | Transportation | F1 Macro | F1 Micro | |
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|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:------:|:------:|:------:|:--------:|:------------:|:------:|:-------------------:|:--------------:|:--------:|:--------:| |
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| 0.2425 | 1.0 | 629 | 0.0989 | 0.9661 | 0.8889 | 0.8030 | 0.9068 | 0.3358 | 0.9152 | 0.8045 | 0.9843 | 0.8291 | 0.9222 | 0.8356 | 0.9001 | |
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| 0.0596 | 2.0 | 1258 | 0.0885 | 0.9807 | 0.9446 | 0.9283 | 0.9620 | 0.4786 | 0.9462 | 0.8665 | 0.9810 | 0.8690 | 0.9885 | 0.8945 | 0.9367 | |
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| 0.0376 | 3.0 | 1887 | 0.0899 | 0.9828 | 0.9284 | 0.9483 | 0.9765 | 0.6406 | 0.9458 | 0.8720 | 0.9865 | 0.8783 | 1.0 | 0.9159 | 0.9423 | |
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| 0.0257 | 4.0 | 2516 | 0.0919 | 0.9875 | 0.9362 | 0.9766 | 0.9805 | 0.6818 | 0.9505 | 0.8827 | 0.9869 | 0.8871 | 1.0 | 0.9270 | 0.9484 | |
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| 0.0172 | 5.0 | 3145 | 0.0873 | 0.9883 | 0.9446 | 0.9785 | 0.9765 | 0.7063 | 0.9538 | 0.8807 | 0.9851 | 0.8886 | 1.0 | 0.9302 | 0.9499 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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