Trained BERT binary classifier

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: bert-binary-clf
+  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. -->
+
+# bert-binary-clf
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1279
+- Accuracy: 0.9748
+- Precision: 0.9825
+- Recall: 0.9655
+- F1: 0.9739
+
+## 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
+- 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
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.4681        | 1.0   | 30   | 0.3535          | 0.8824   | 0.8143    | 0.9828 | 0.8906 |
+| 0.2283        | 2.0   | 60   | 0.1883          | 0.9412   | 0.9322    | 0.9483 | 0.9402 |
+| 0.1144        | 3.0   | 90   | 0.1279          | 0.9748   | 0.9825    | 0.9655 | 0.9739 |
+| 0.0695        | 4.0   | 120  | 0.1230          | 0.9580   | 0.9818    | 0.9310 | 0.9558 |
+
+
+### Framework versions
+
+- Transformers 4.57.1
+- Pytorch 2.8.0+cu126
+- Datasets 4.0.0
+- Tokenizers 0.22.1

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