End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google-bert/bert-base-cased
+tags:
+- generated_from_trainer
+datasets:
+- biobert_json
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-base-cased-finetuned-ner
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: biobert_json
+      type: biobert_json
+      config: Biobert_json
+      split: validation
+      args: Biobert_json
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.941812865497076
+    - name: Recall
+      type: recall
+      value: 0.966852487135506
+    - name: F1
+      type: f1
+      value: 0.9541684299619129
+    - name: Accuracy
+      type: accuracy
+      value: 0.9754933560689555
+---
+
+<!-- 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. -->
+
+# bert-base-cased-finetuned-ner
+
+This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on the biobert_json dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1119
+- Precision: 0.9418
+- Recall: 0.9669
+- F1: 0.9542
+- Accuracy: 0.9755
+
+## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.1824        | 1.0   | 1224 | 0.1170          | 0.9227    | 0.9563 | 0.9392 | 0.9686   |
+| 0.1162        | 2.0   | 2448 | 0.1138          | 0.9277    | 0.9654 | 0.9462 | 0.9717   |
+| 0.0756        | 3.0   | 3672 | 0.1025          | 0.9398    | 0.9685 | 0.9540 | 0.9751   |
+| 0.051         | 4.0   | 4896 | 0.1076          | 0.9425    | 0.9691 | 0.9556 | 0.9759   |
+| 0.0423        | 5.0   | 6120 | 0.1119          | 0.9418    | 0.9669 | 0.9542 | 0.9755   |
+
+
+### Framework versions
+
+- Transformers 4.46.2
+- Pytorch 2.5.1
+- Datasets 3.1.0
+- Tokenizers 0.20.3

runs/Nov15_16-38-40_DESKTOP-P79TL96/events.out.tfevents.1731706722.DESKTOP-P79TL96

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