| ---
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| library_name: transformers
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| license: apache-2.0
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| base_model: bert-base-uncased
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| tags:
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| - generated_from_trainer
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| metrics:
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| - accuracy
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| - f1
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| model-index:
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| - name: test
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| results: []
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| ---
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|
|
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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| should probably proofread and complete it, then remove this comment. -->
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|
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| # test
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| This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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| It achieves the following results on the evaluation set:
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| - Loss: 0.8066
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| - Accuracy: 0.8412
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| - F1: 0.8864
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|
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| ## Model description
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| More information needed
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|
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| ## Intended uses & limitations
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| More information needed
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|
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| ## Training and evaluation data
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| More information needed
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|
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| ## Training procedure
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|
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| ### Training hyperparameters
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| The following hyperparameters were used during training:
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| - learning_rate: 5e-05
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| - train_batch_size: 16
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| - eval_batch_size: 16
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| - seed: 42
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| - gradient_accumulation_steps: 4
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| - total_train_batch_size: 64
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| - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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| - lr_scheduler_type: cosine
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| - num_epochs: 8
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| - mixed_precision_training: Native AMP
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|
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| ### Training results
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| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| | 0.5381 | 1.0 | 58 | 0.4061 | 0.8214 | 0.8669 |
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| | 0.3253 | 2.0 | 116 | 0.3933 | 0.8209 | 0.8625 |
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| | 0.1943 | 3.0 | 174 | 0.4147 | 0.8307 | 0.8734 |
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| | 0.099 | 4.0 | 232 | 0.7017 | 0.8180 | 0.8739 |
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| | 0.0578 | 5.0 | 290 | 0.7371 | 0.8348 | 0.8799 |
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| | 0.0305 | 6.0 | 348 | 0.7759 | 0.8429 | 0.8879 |
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| | 0.0187 | 7.0 | 406 | 0.8006 | 0.8394 | 0.8851 |
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| | 0.0161 | 8.0 | 464 | 0.8066 | 0.8412 | 0.8864 |
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| ### Framework versions
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| - Transformers 4.54.0
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| - Pytorch 2.7.1+cu118
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| - Datasets 3.0.2
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| - Tokenizers 0.21.2
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| |
