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--- |
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language: |
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- vi |
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base_model: vinai/phobert-base-v2 |
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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-v2_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-v2_baseline_words |
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This model is a fine-tuned version of [vinai/phobert-base-v2](https://huggingface.co/vinai/phobert-base-v2) on the covid19_ner dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0874 |
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- Patient Id: 0.9824 |
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- Name: 0.9415 |
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- Gender: 0.9647 |
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- Age: 0.9502 |
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- Job: 0.8000 |
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- Location: 0.9509 |
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- Organization: 0.9148 |
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- Date: 0.9860 |
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- Symptom And Disease: 0.8863 |
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- Transportation: 1.0 |
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- F1 Macro: 0.9377 |
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- F1 Micro: 0.9503 |
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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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| 0.4337 | 1.0 | 629 | 0.1664 | 0.9739 | 0.9446 | 0.7794 | 0.9010 | 0.0 | 0.9341 | 0.8413 | 0.9851 | 0.8585 | 0.9885 | 0.8206 | 0.9172 | |
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| 0.1019 | 2.0 | 1258 | 0.1071 | 0.9770 | 0.9340 | 0.9640 | 0.9644 | 0.5412 | 0.9460 | 0.8823 | 0.9865 | 0.8771 | 1.0 | 0.9072 | 0.9402 | |
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| 0.0639 | 3.0 | 1887 | 0.0952 | 0.9797 | 0.928 | 0.9647 | 0.9682 | 0.5799 | 0.9488 | 0.9094 | 0.9847 | 0.8814 | 1.0 | 0.9145 | 0.9445 | |
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| 0.0454 | 4.0 | 2516 | 0.0873 | 0.9820 | 0.9365 | 0.9663 | 0.9632 | 0.7734 | 0.9537 | 0.9075 | 0.9851 | 0.8832 | 1.0 | 0.9351 | 0.9503 | |
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| 0.0365 | 5.0 | 3145 | 0.0874 | 0.9824 | 0.9415 | 0.9647 | 0.9502 | 0.8000 | 0.9509 | 0.9148 | 0.9860 | 0.8863 | 1.0 | 0.9377 | 0.9503 | |
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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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