Model save

README.md

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+---
+base_model: dmis-lab/biobert-v1.1
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: phibert-finetuned-ner-new-1
+  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. -->
+
+# phibert-finetuned-ner-new-1
+
+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.
+It achieves the following results on the evaluation set:
+- Loss: 0.0184
+- Precision: 0.9485
+- Recall: 0.9533
+- F1: 0.9509
+- Accuracy: 0.9963
+
+## 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: 2e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.044         | 1.0   | 5915  | 0.0236          | 0.9014    | 0.9109 | 0.9061 | 0.9937   |
+| 0.0266        | 2.0   | 11830 | 0.0209          | 0.9095    | 0.9271 | 0.9182 | 0.9943   |
+| 0.0101        | 3.0   | 17745 | 0.0191          | 0.9335    | 0.9452 | 0.9393 | 0.9955   |
+| 0.0104        | 4.0   | 23660 | 0.0181          | 0.9349    | 0.9483 | 0.9415 | 0.9959   |
+| 0.0039        | 5.0   | 29575 | 0.0184          | 0.9485    | 0.9533 | 0.9509 | 0.9963   |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.4
+- Tokenizers 0.13.3