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README.md

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+---
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: biobert-base-cased-v1.2-finetuned-ner
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# biobert-base-cased-v1.2-finetuned-ner
+
+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 None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2662
+- Precision: 0.8204
+- Recall: 0.8577
+- F1: 0.8386
+- Accuracy: 0.9521
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 3e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0189        | 1.0   | 680  | 0.2662          | 0.8204    | 0.8577 | 0.8386 | 0.9521   |
+| 0.0141        | 2.0   | 1360 | 0.3010          | 0.8188    | 0.8407 | 0.8296 | 0.9491   |
+| 0.0119        | 3.0   | 2040 | 0.3169          | 0.8316    | 0.8463 | 0.8389 | 0.9517   |
+| 0.0101        | 4.0   | 2720 | 0.2845          | 0.8286    | 0.8588 | 0.8434 | 0.9541   |
+
+
+### Framework versions
+
+- Transformers 4.27.2
+- Pytorch 1.13.0+cu117
+- Datasets 2.7.1
+- Tokenizers 0.13.2