End of training

README.md

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+---
+base_model: dmis-lab/biobert-base-cased-v1.2
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: devicebert-base-cased-v1.0
+  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. -->
+
+# devicebert-base-cased-v1.0
+
+This model is a fine-tuned version of [dmis-lab/biobert-base-cased-v1.2](https://huggingface.co/dmis-lab/biobert-base-cased-v1.2) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: nan
+- Precision: 0.9429
+- Recall: 0.9449
+- F1: 0.9439
+- Accuracy: 0.9737
+
+## 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: 1e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 81   | nan             | 0.9429    | 0.9449 | 0.9439 | 0.9737   |
+| No log        | 2.0   | 162  | nan             | 0.9198    | 0.9470 | 0.9332 | 0.9615   |
+| No log        | 3.0   | 243  | nan             | 0.9196    | 0.9449 | 0.9321 | 0.9653   |
+| No log        | 4.0   | 324  | nan             | 0.9379    | 0.9280 | 0.9329 | 0.9719   |
+| No log        | 5.0   | 405  | nan             | 0.9245    | 0.9343 | 0.9294 | 0.9690   |
+| No log        | 6.0   | 486  | nan             | 0.9450    | 0.9470 | 0.9460 | 0.9747   |
+| 0.0945        | 7.0   | 567  | nan             | 0.9446    | 0.9386 | 0.9416 | 0.9747   |
+| 0.0945        | 8.0   | 648  | nan             | 0.9189    | 0.9364 | 0.9276 | 0.9672   |
+| 0.0945        | 9.0   | 729  | nan             | 0.9245    | 0.9343 | 0.9294 | 0.9662   |
+| 0.0945        | 10.0  | 810  | nan             | 0.9407    | 0.9407 | 0.9407 | 0.9728   |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.2
+- Tokenizers 0.19.1

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