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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/multi-train-distemist-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/multi-train-distemist-dev-ner |
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type: Rodrigo1771/multi-train-distemist-dev-ner |
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config: MultiTrainDisTEMISTDevNER |
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split: validation |
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args: MultiTrainDisTEMISTDevNER |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.32143181611701643 |
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- name: Recall |
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type: recall |
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value: 0.8277959756668226 |
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- name: F1 |
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type: f1 |
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value: 0.46305870034683594 |
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- name: Accuracy |
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type: accuracy |
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value: 0.8559776451929613 |
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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/multi-train-distemist-dev-ner dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9499 |
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- Precision: 0.3214 |
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- Recall: 0.8278 |
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- F1: 0.4631 |
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- Accuracy: 0.8560 |
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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: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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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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| 0.2596 | 0.9997 | 1701 | 0.4319 | 0.2617 | 0.7866 | 0.3927 | 0.8359 | |
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| 0.1853 | 2.0 | 3403 | 0.3841 | 0.3142 | 0.7829 | 0.4485 | 0.8645 | |
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| 0.1254 | 2.9997 | 5104 | 0.6410 | 0.3055 | 0.8088 | 0.4435 | 0.8436 | |
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| 0.0823 | 4.0 | 6806 | 0.7242 | 0.2964 | 0.8074 | 0.4336 | 0.8436 | |
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| 0.0597 | 4.9997 | 8507 | 0.7756 | 0.3133 | 0.7948 | 0.4495 | 0.8502 | |
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| 0.0446 | 6.0 | 10209 | 0.8561 | 0.3137 | 0.8037 | 0.4513 | 0.8483 | |
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| 0.0325 | 6.9997 | 11910 | 0.9499 | 0.3214 | 0.8278 | 0.4631 | 0.8560 | |
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| 0.022 | 8.0 | 13612 | 1.0452 | 0.3129 | 0.8222 | 0.4533 | 0.8510 | |
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| 0.017 | 8.9997 | 15313 | 1.1025 | 0.3133 | 0.8180 | 0.4531 | 0.8524 | |
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| 0.0135 | 9.9971 | 17010 | 1.1188 | 0.3145 | 0.8224 | 0.4550 | 0.8526 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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