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+ ---
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+ tags:
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+ - generated_from_trainer
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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: phibert-finetuned-ner
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+ results: []
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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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+ # phibert-finetuned-ner
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+
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+ This model is a fine-tuned version of [dmis-lab/biobert-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0170
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+ - Precision: 0.9496
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+ - Recall: 0.9538
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+ - F1: 0.9517
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+ - Accuracy: 0.9966
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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: 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: 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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+ | 0.0276 | 1.0 | 5732 | 0.0214 | 0.9313 | 0.9271 | 0.9292 | 0.9958 |
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+ | 0.0138 | 2.0 | 11464 | 0.0171 | 0.9376 | 0.9484 | 0.9430 | 0.9966 |
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+ | 0.0072 | 3.0 | 17196 | 0.0170 | 0.9496 | 0.9538 | 0.9517 | 0.9966 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.25.1
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+ - Pytorch 1.13.1+cu116
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+ - Datasets 2.8.0
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+ - Tokenizers 0.13.2