Model save

README.md

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+---
+library_name: transformers
+base_model: dmis-lab/biobert-base-cased-v1.2
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+model-index:
+- name: ade_biobert_output
+  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. -->
+
+# ade_biobert_output
+
+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: 0.4138
+- Precision: 0.8945
+- Recall: 0.8822
+- F1: 0.8853
+- Recall Positive: 0.8887
+- Recall Negative: 0.8798
+
+## 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: 5e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | F1     | Recall Positive | Recall Negative |
+|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:---------------:|:---------------:|
+| 0.4983        | 0.1063 | 500  | 0.5789          | 0.8609    | 0.7602 | 0.7700 | 0.9858          | 0.6640          |
+| 0.4389        | 0.2126 | 1000 | 0.6829          | 0.8700    | 0.8639 | 0.8547 | 0.6031          | 0.9751          |
+| 0.5353        | 0.3189 | 1500 | 0.4000          | 0.8974    | 0.8903 | 0.8922 | 0.8862          | 0.8921          |
+| 0.6367        | 0.4253 | 2000 | 0.6262          | 0.4915    | 0.7011 | 0.5779 | 0.0             | 1.0             |
+| 0.623         | 0.5316 | 2500 | 0.6189          | 0.4915    | 0.7011 | 0.5779 | 0.0             | 1.0             |
+| 0.6653        | 0.6379 | 3000 | 0.6122          | 0.4915    | 0.7011 | 0.5779 | 0.0             | 1.0             |
+
+
+### Framework versions
+
+- Transformers 4.55.0
+- Pytorch 2.8.0
+- Datasets 4.0.0
+- Tokenizers 0.21.4

model.safetensors

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