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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/combined-train-drugtemist-dev-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/combined-train-drugtemist-dev-ner |
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type: Rodrigo1771/combined-train-drugtemist-dev-ner |
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config: CombinedTrainDrugTEMISTDevNER |
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split: validation |
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args: CombinedTrainDrugTEMISTDevNER |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.09532555790247038 |
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- name: Recall |
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type: recall |
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value: 0.9540441176470589 |
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- name: F1 |
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type: f1 |
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value: 0.17333222008850296 |
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- name: Accuracy |
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type: accuracy |
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value: 0.7932840841995413 |
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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/combined-train-drugtemist-dev-ner dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0503 |
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- Precision: 0.0953 |
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- Recall: 0.9540 |
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- F1: 0.1733 |
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- Accuracy: 0.7933 |
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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 | 0.9988 | 425 | 0.6611 | 0.0883 | 0.9292 | 0.1613 | 0.7850 | |
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| 0.3349 | 2.0 | 851 | 0.9204 | 0.0787 | 0.9301 | 0.1451 | 0.7551 | |
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| 0.1788 | 2.9988 | 1276 | 0.9545 | 0.0844 | 0.9329 | 0.1549 | 0.7645 | |
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| 0.1227 | 4.0 | 1702 | 1.0924 | 0.0885 | 0.9412 | 0.1618 | 0.7692 | |
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| 0.0856 | 4.9988 | 2127 | 1.0503 | 0.0953 | 0.9540 | 0.1733 | 0.7933 | |
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| 0.0597 | 6.0 | 2553 | 1.2642 | 0.0912 | 0.9449 | 0.1663 | 0.7788 | |
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| 0.0597 | 6.9988 | 2978 | 1.3262 | 0.0928 | 0.9485 | 0.1690 | 0.7829 | |
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| 0.0458 | 8.0 | 3404 | 1.3698 | 0.0926 | 0.9522 | 0.1688 | 0.7849 | |
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| 0.0343 | 8.9988 | 3829 | 1.4433 | 0.0907 | 0.9449 | 0.1655 | 0.7822 | |
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| 0.0292 | 9.9882 | 4250 | 1.4862 | 0.0914 | 0.9458 | 0.1667 | 0.7821 | |
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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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