End of training

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_BioNLP13CG_NER_new
+  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_BioNLP13CG_NER_new
+
+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: 0.1721
+- Precision: 0.8444
+- Recall: 0.8396
+- F1: 0.8420
+- Accuracy: 0.9571
+
+## 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: 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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 191  | 0.2112          | 0.8333    | 0.8134 | 0.8232 | 0.9507   |
+| No log        | 2.0   | 382  | 0.1744          | 0.8304    | 0.8400 | 0.8352 | 0.9557   |
+| 0.3204        | 3.0   | 573  | 0.1721          | 0.8444    | 0.8396 | 0.8420 | 0.9571   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.0