End of training

README.md

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+---
+base_model: medicalai/ClinicalBERT
+tags:
+- generated_from_trainer
+model-index:
+- name: JNLPBA_ClinicalBERT_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. -->
+
+# JNLPBA_ClinicalBERT_NER
+
+This model is a fine-tuned version of [medicalai/ClinicalBERT](https://huggingface.co/medicalai/ClinicalBERT) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1723
+- Seqeval classification report:               precision    recall  f1-score   support
+
+         DNA       0.72      0.81      0.77      1351
+         RNA       0.71      0.86      0.78       723
+   cell_line       0.84      0.74      0.78       582
+   cell_type       0.72      0.75      0.73      5623
+     protein       0.85      0.85      0.85      3501
+
+   micro avg       0.76      0.79      0.78     11780
+   macro avg       0.77      0.80      0.78     11780
+weighted avg       0.76      0.79      0.78     11780
+
+
+## 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
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- 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 | Seqeval classification report                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
+|:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
+| 0.336         | 1.0   | 582  | 0.1930          |               precision    recall  f1-score   support
+
+         DNA       0.72      0.77      0.75      1351
+         RNA       0.70      0.84      0.77       723
+   cell_line       0.85      0.70      0.77       582
+   cell_type       0.71      0.68      0.69      5623
+     protein       0.85      0.80      0.83      3501
+
+   micro avg       0.76      0.74      0.75     11780
+   macro avg       0.77      0.76      0.76     11780
+weighted avg       0.76      0.74      0.75     11780
+ |
+| 0.1841        | 2.0   | 1164 | 0.1762          |               precision    recall  f1-score   support
+
+         DNA       0.73      0.78      0.76      1351
+         RNA       0.70      0.87      0.78       723
+   cell_line       0.86      0.71      0.78       582
+   cell_type       0.71      0.73      0.72      5623
+     protein       0.86      0.83      0.84      3501
+
+   micro avg       0.76      0.77      0.77     11780
+   macro avg       0.77      0.78      0.78     11780
+weighted avg       0.77      0.77      0.77     11780
+ |
+| 0.1582        | 3.0   | 1746 | 0.1723          |               precision    recall  f1-score   support
+
+         DNA       0.72      0.81      0.77      1351
+         RNA       0.71      0.86      0.78       723
+   cell_line       0.84      0.74      0.78       582
+   cell_type       0.72      0.75      0.73      5623
+     protein       0.85      0.85      0.85      3501
+
+   micro avg       0.76      0.79      0.78     11780
+   macro avg       0.77      0.80      0.78     11780
+weighted avg       0.76      0.79      0.78     11780
+ |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.15.0
+- Tokenizers 0.15.0