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--- |
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language: |
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- vi |
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base_model: vinai/phobert-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: phobert-base_baseline_words |
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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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# phobert-base_baseline_words |
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This model is a fine-tuned version of [vinai/phobert-base](https://huggingface.co/vinai/phobert-base) on the covid19_ner dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0829 |
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- Patient Id: 0.9848 |
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- Name: 0.9421 |
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- Gender: 0.9570 |
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- Age: 0.9766 |
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- Job: 0.8095 |
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- Location: 0.9448 |
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- Organization: 0.9078 |
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- Date: 0.9869 |
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- Symptom And Disease: 0.8923 |
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- Transportation: 0.9943 |
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- F1 Macro: 0.9396 |
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- F1 Micro: 0.9498 |
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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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| 0.2964 | 1.0 | 629 | 0.1215 | 0.9689 | 0.9534 | 0.9107 | 0.8987 | 0.5357 | 0.9350 | 0.8368 | 0.9856 | 0.8584 | 0.9667 | 0.8850 | 0.9251 | |
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| 0.068 | 2.0 | 1258 | 0.0890 | 0.9844 | 0.9479 | 0.9487 | 0.9723 | 0.6167 | 0.9377 | 0.8815 | 0.9860 | 0.8835 | 0.9886 | 0.9147 | 0.9409 | |
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| 0.0441 | 3.0 | 1887 | 0.0847 | 0.9828 | 0.9446 | 0.9554 | 0.9737 | 0.7570 | 0.9445 | 0.9062 | 0.9874 | 0.8909 | 0.9943 | 0.9337 | 0.9482 | |
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| 0.0327 | 4.0 | 2516 | 0.0859 | 0.9859 | 0.9449 | 0.9570 | 0.9765 | 0.7778 | 0.9451 | 0.9062 | 0.9874 | 0.8914 | 0.9943 | 0.9366 | 0.9495 | |
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| 0.0259 | 5.0 | 3145 | 0.0829 | 0.9848 | 0.9421 | 0.9570 | 0.9766 | 0.8095 | 0.9448 | 0.9078 | 0.9869 | 0.8923 | 0.9943 | 0.9396 | 0.9498 | |
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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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