Training complete

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: biobert-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-finetuned-ner
+
+This model is a fine-tuned version of [dmis-lab/biobert-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4144
+- Precision: 0.6250
+- Recall: 0.6815
+- F1: 0.6520
+- Accuracy: 0.8601
+
+## 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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 305  | 0.4106          | 0.6036    | 0.6678 | 0.6340 | 0.8556   |
+| 0.4536        | 2.0   | 610  | 0.3975          | 0.6211    | 0.6825 | 0.6503 | 0.8601   |
+| 0.4536        | 3.0   | 915  | 0.4144          | 0.6250    | 0.6815 | 0.6520 | 0.8601   |
+
+
+### Framework versions
+
+- Transformers 4.40.1
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1