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--- |
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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: results |
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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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# results |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0488 |
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- Accuracy: 0.8207 |
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- Precision: 0.9268 |
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- Recall: 0.8840 |
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- F1: 0.9030 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-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: 2 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 20 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.0242 | 0.9971 | 173 | 0.0552 | 0.8452 | 0.8964 | 0.8905 | 0.8883 | |
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| 0.0298 | 2.0 | 347 | 0.0488 | 0.8207 | 0.9268 | 0.8840 | 0.9030 | |
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| 0.0236 | 2.9971 | 520 | 0.0484 | 0.8214 | 0.9338 | 0.8680 | 0.8971 | |
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| 0.0298 | 4.0 | 694 | 0.0498 | 0.8251 | 0.9357 | 0.8719 | 0.9004 | |
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| 0.0232 | 4.9971 | 867 | 0.0477 | 0.8281 | 0.9381 | 0.8732 | 0.9020 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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