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+ ---
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - ncbi_disease
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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: biobert-base-cased-v1.2-finetuned-ner
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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: ncbi_disease
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+ type: ncbi_disease
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+ args: ncbi_disease
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+ metrics:
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+ - name: Precision
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+ type: precision
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+ value: 0.8396334478808706
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+ - name: Recall
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+ type: recall
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+ value: 0.8731387730792138
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+ - name: F1
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+ type: f1
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+ value: 0.856058394160584
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9824805769647444
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+ ---
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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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+
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+ # biobert-base-cased-v1.2-finetuned-ner
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+
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+ This model is a fine-tuned version of [dmis-lab/biobert-base-cased-v1.2](https://huggingface.co/dmis-lab/biobert-base-cased-v1.2) on the ncbi_disease dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0706
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+ - Precision: 0.8396
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+ - Recall: 0.8731
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+ - F1: 0.8561
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+ - Accuracy: 0.9825
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 16
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+ - eval_batch_size: 16
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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: 3
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+
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+ ### Training results
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+
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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 | 340 | 0.0691 | 0.8190 | 0.7868 | 0.8026 | 0.9777 |
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+ | 0.101 | 2.0 | 680 | 0.0700 | 0.8334 | 0.8553 | 0.8442 | 0.9807 |
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+ | 0.0244 | 3.0 | 1020 | 0.0706 | 0.8396 | 0.8731 | 0.8561 | 0.9825 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.19.4
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+ - Pytorch 1.11.0+cu113
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+ - Datasets 2.3.0
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+ - Tokenizers 0.12.1