End of training

README.md

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+---
+license: cc0-1.0
+base_model: bionlp/bluebert_pubmed_mimic_uncased_L-12_H-768_A-12
+tags:
+- generated_from_trainer
+model-index:
+- name: BC5CDR_BlueBERT_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_BlueBERT_NER
+
+This model is a fine-tuned version of [bionlp/bluebert_pubmed_mimic_uncased_L-12_H-768_A-12](https://huggingface.co/bionlp/bluebert_pubmed_mimic_uncased_L-12_H-768_A-12) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0944
+- Seqeval classification report:               precision    recall  f1-score   support
+
+    Chemical       0.84      0.89      0.87      7079
+     Disease       0.82      0.85      0.83      4968
+
+   micro avg       0.83      0.87      0.85     12047
+   macro avg       0.83      0.87      0.85     12047
+weighted avg       0.83      0.87      0.85     12047
+
+
+## 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  | 0.1111          |               precision    recall  f1-score   support
+
+    Chemical       0.82      0.86      0.84      7079
+     Disease       0.76      0.83      0.80      4968
+
+   micro avg       0.79      0.85      0.82     12047
+   macro avg       0.79      0.85      0.82     12047
+weighted avg       0.79      0.85      0.82     12047
+ |
+| No log        | 2.0   | 286  | 0.0987          |               precision    recall  f1-score   support
+
+    Chemical       0.83      0.89      0.86      7079
+     Disease       0.78      0.86      0.82      4968
+
+   micro avg       0.81      0.88      0.84     12047
+   macro avg       0.80      0.87      0.84     12047
+weighted avg       0.81      0.88      0.84     12047
+ |
+| No log        | 3.0   | 429  | 0.0944          |               precision    recall  f1-score   support
+
+    Chemical       0.84      0.89      0.87      7079
+     Disease       0.82      0.85      0.83      4968
+
+   micro avg       0.83      0.87      0.85     12047
+   macro avg       0.83      0.87      0.85     12047
+weighted avg       0.83      0.87      0.85     12047
+ |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.15.0
+- Tokenizers 0.15.0