Training complete

README.md

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+---
+library_name: transformers
+license: mit
+base_model: emilyalsentzer/Bio_ClinicalBERT
+tags:
+- generated_from_trainer
+datasets:
+- ncbi_disease
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-finetuned-ner
+ results:
+ - task:
+ name: Token Classification
+ type: token-classification
+ dataset:
+ name: ncbi_disease
+ type: ncbi_disease
+ config: ncbi_disease
+ split: validation
+ args: ncbi_disease
+ metrics:
+ - name: Precision
+ type: precision
+ value: 0.8187274909963985
+ - name: Recall
+ type: recall
+ value: 0.866581956797967
+ - name: F1
+ type: f1
+ value: 0.8419753086419753
+ - name: Accuracy
+ type: accuracy
+ value: 0.9840901352648033
+---
+
+<!-- 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-finetuned-ner
+
+This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on the ncbi_disease dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0860
+- Precision: 0.8187
+- Recall: 0.8666
+- F1: 0.8420
+- Accuracy: 0.9841
+
+## 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: 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 |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0104 | 1.0 | 680 | 0.0804 | 0.7848 | 0.8526 | 0.8173 | 0.9829 |
+| 0.0094 | 2.0 | 1360 | 0.0777 | 0.8350 | 0.8424 | 0.8387 | 0.9842 |
+| 0.0037 | 3.0 | 2040 | 0.0860 | 0.8187 | 0.8666 | 0.8420 | 0.9841 |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.0+cu121
+- Datasets 3.0.0
+- Tokenizers 0.19.1

runs/Sep12_04-48-50_e760ed30d532/events.out.tfevents.1726116734.e760ed30d532.772.1

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