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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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- precision |
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- recall |
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- accuracy |
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model-index: |
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- name: classify |
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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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# classify |
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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: 0.5723 |
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- Precision: 0.0 |
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- Recall: 0.0 |
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- F1 Binary: 0.0 |
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- Accuracy: 0.7429 |
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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: 0.0003 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 0 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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- optimizer: Use OptimizerNames.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: linear |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 Binary | Accuracy | |
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|:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:---------:|:--------:| |
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| No log | 0 | 0 | 0.7028 | 0.2437 | 0.7160 | 0.3636 | 0.3556 | |
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| 0.6 | 2.8181 | 1000 | 0.5779 | 0.0 | 0.0 | 0.0 | 0.7429 | |
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| 0.5522 | 5.6347 | 2000 | 0.5709 | 0.0 | 0.0 | 0.0 | 0.7429 | |
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| 0.5582 | 8.4513 | 3000 | 0.5709 | 0.0 | 0.0 | 0.0 | 0.7429 | |
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| 0.5791 | 11.2680 | 4000 | 0.5703 | 0.0 | 0.0 | 0.0 | 0.7429 | |
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| 0.5895 | 14.0846 | 5000 | 0.5701 | 0.0 | 0.0 | 0.0 | 0.7429 | |
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| 0.5629 | 16.9027 | 6000 | 0.5730 | 0.0 | 0.0 | 0.0 | 0.7429 | |
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| 0.5841 | 19.7193 | 7000 | 0.5723 | 0.0 | 0.0 | 0.0 | 0.7429 | |
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### Framework versions |
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- Transformers 4.48.1 |
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- Pytorch 2.3.0 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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