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-all
+  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-all
+
+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: 0.0600
+- Accuracy: 0.9902
+- Precision: 0.9964
+- Recall: 0.9833
+- F1: 0.9898
+
+## 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: 8
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.1287        | 1.0   | 433  | 0.0515          | 0.9884   | 0.9811    | 0.9952 | 0.9881 |
+| 0.034         | 2.0   | 866  | 0.0732          | 0.9827   | 0.9867    | 0.9773 | 0.9820 |
+| 0.0163        | 3.0   | 1299 | 0.0600          | 0.9902   | 0.9964    | 0.9833 | 0.9898 |
+| 0.0087        | 4.0   | 1732 | 0.0842          | 0.9861   | 0.9927    | 0.9785 | 0.9855 |
+| 0.0024        | 5.0   | 2165 | 0.0748          | 0.9884   | 0.9811    | 0.9952 | 0.9881 |
+
+
+### Framework versions
+
+- Transformers 4.57.1
+- Pytorch 2.8.0+cu126
+- Datasets 4.0.0
+- Tokenizers 0.22.1

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