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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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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: patent-bert-classifier |
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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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# patent-bert-classifier |
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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: 0.9548 |
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- Accuracy: 0.681 |
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- F1: 0.6557 |
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- Precision: 0.6499 |
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- Recall: 0.681 |
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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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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 5 |
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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 | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 1.0317 | 1.0 | 1563 | 0.9973 | 0.6568 | 0.6323 | 0.6319 | 0.6568 | |
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| 0.8575 | 2.0 | 3126 | 0.9251 | 0.6888 | 0.6641 | 0.6592 | 0.6888 | |
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| 0.6298 | 3.0 | 4689 | 0.9880 | 0.6736 | 0.6604 | 0.6533 | 0.6736 | |
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| 0.4886 | 4.0 | 6252 | 1.0900 | 0.6764 | 0.6678 | 0.6615 | 0.6764 | |
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| 0.3765 | 5.0 | 7815 | 1.1712 | 0.6688 | 0.6601 | 0.6545 | 0.6688 | |
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### Framework versions |
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- Transformers 4.57.0 |
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- Pytorch 2.8.0+cu128 |
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- Datasets 4.2.0 |
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- Tokenizers 0.22.1 |
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