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--- |
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language: |
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- vi |
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base_model: vinai/phobert-large |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: phobert-large_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-large_baseline_words |
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This model is a fine-tuned version of [vinai/phobert-large](https://huggingface.co/vinai/phobert-large) on the covid19_ner dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0943 |
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- Patient Id: 0.9863 |
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- Name: 0.9542 |
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- Gender: 0.9664 |
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- Age: 0.9633 |
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- Job: 0.8300 |
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- Location: 0.9521 |
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- Organization: 0.9188 |
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- Date: 0.9842 |
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- Symptom And Disease: 0.8773 |
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- Transportation: 1.0 |
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- F1 Macro: 0.9433 |
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- F1 Micro: 0.9521 |
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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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| 0.2801 | 1.0 | 629 | 0.0981 | 0.9840 | 0.9455 | 0.9045 | 0.9010 | 0.5837 | 0.9265 | 0.8726 | 0.9812 | 0.8611 | 0.9831 | 0.8943 | 0.9266 | |
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| 0.0446 | 2.0 | 1258 | 0.0897 | 0.9863 | 0.9549 | 0.9501 | 0.9722 | 0.7833 | 0.9355 | 0.8907 | 0.9852 | 0.8814 | 0.9721 | 0.9312 | 0.9434 | |
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| 0.0283 | 3.0 | 1887 | 0.0809 | 0.9867 | 0.9516 | 0.9551 | 0.9695 | 0.7857 | 0.9487 | 0.9086 | 0.9860 | 0.8845 | 1.0 | 0.9376 | 0.9502 | |
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| 0.0198 | 4.0 | 2516 | 0.0905 | 0.9863 | 0.9542 | 0.9647 | 0.9633 | 0.8287 | 0.9483 | 0.9159 | 0.9842 | 0.8897 | 1.0 | 0.9435 | 0.9516 | |
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| 0.0134 | 5.0 | 3145 | 0.0943 | 0.9863 | 0.9542 | 0.9664 | 0.9633 | 0.8300 | 0.9521 | 0.9188 | 0.9842 | 0.8773 | 1.0 | 0.9433 | 0.9521 | |
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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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