End of training

README.md

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+---
+base_model: medicalai/ClinicalBERT
+tags:
+- generated_from_trainer
+model-index:
+- name: BC5CDR_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. -->
+
+# BC5CDR_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: 0.1107
+- Seqeval classification report:               precision    recall  f1-score   support
+
+    Chemical       0.71      0.73      0.72     10493
+     Disease       0.82      0.82      0.82      6944
+
+   micro avg       0.75      0.77      0.76     17437
+   macro avg       0.76      0.78      0.77     17437
+weighted avg       0.75      0.77      0.76     17437
+
+
+## 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                                                                                                                                                                                                                                                                                                          |
+|:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
+| No log        | 1.0   | 143  | 0.1255          |               precision    recall  f1-score   support
+
+    Chemical       0.67      0.68      0.68     10493
+     Disease       0.79      0.78      0.78      6944
+
+   micro avg       0.72      0.72      0.72     17437
+   macro avg       0.73      0.73      0.73     17437
+weighted avg       0.72      0.72      0.72     17437
+ |
+| No log        | 2.0   | 286  | 0.1160          |               precision    recall  f1-score   support
+
+    Chemical       0.69      0.71      0.70     10493
+     Disease       0.77      0.83      0.80      6944
+
+   micro avg       0.72      0.76      0.74     17437
+   macro avg       0.73      0.77      0.75     17437
+weighted avg       0.72      0.76      0.74     17437
+ |
+| No log        | 3.0   | 429  | 0.1107          |               precision    recall  f1-score   support
+
+    Chemical       0.71      0.73      0.72     10493
+     Disease       0.82      0.82      0.82      6944
+
+   micro avg       0.75      0.77      0.76     17437
+   macro avg       0.76      0.78      0.77     17437
+weighted avg       0.75      0.77      0.76     17437
+ |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.15.0
+- Tokenizers 0.15.0