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--- |
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license: apache-2.0 |
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base_model: PlanTL-GOB-ES/bsc-bio-ehr-es |
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tags: |
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- token-classification |
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- generated_from_trainer |
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datasets: |
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- Rodrigo1771/symptemist-ner |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: output |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: Rodrigo1771/symptemist-ner |
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type: Rodrigo1771/symptemist-ner |
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config: SympTEMIST NER |
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split: validation |
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args: SympTEMIST NER |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.6675139806812405 |
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- name: Recall |
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type: recall |
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value: 0.7186644772851669 |
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- name: F1 |
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type: f1 |
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value: 0.6921454928835002 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9483461131252205 |
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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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# output |
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This model is a fine-tuned version of [PlanTL-GOB-ES/bsc-bio-ehr-es](https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es) on the Rodrigo1771/symptemist-ner dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2747 |
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- Precision: 0.6675 |
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- Recall: 0.7187 |
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- F1: 0.6921 |
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- Accuracy: 0.9483 |
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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: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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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: 10.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 150 | 0.1504 | 0.5091 | 0.6409 | 0.5675 | 0.9456 | |
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| No log | 2.0 | 300 | 0.1547 | 0.5881 | 0.6995 | 0.639 | 0.9462 | |
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| No log | 3.0 | 450 | 0.1618 | 0.6237 | 0.6984 | 0.6589 | 0.9476 | |
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| 0.126 | 4.0 | 600 | 0.1920 | 0.6154 | 0.7181 | 0.6628 | 0.9451 | |
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| 0.126 | 5.0 | 750 | 0.2102 | 0.6561 | 0.7028 | 0.6786 | 0.9488 | |
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| 0.126 | 6.0 | 900 | 0.2414 | 0.6443 | 0.7088 | 0.6750 | 0.9467 | |
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| 0.0251 | 7.0 | 1050 | 0.2500 | 0.6588 | 0.7061 | 0.6816 | 0.9492 | |
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| 0.0251 | 8.0 | 1200 | 0.2642 | 0.6440 | 0.7307 | 0.6846 | 0.9474 | |
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| 0.0251 | 9.0 | 1350 | 0.2747 | 0.6675 | 0.7187 | 0.6921 | 0.9483 | |
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| 0.0091 | 10.0 | 1500 | 0.2767 | 0.6595 | 0.7187 | 0.6878 | 0.9488 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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