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--- |
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license: apache-2.0 |
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base_model: bert-large-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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- f1 |
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- accuracy |
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model-index: |
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- name: BERT_large_with_preprocessing_grid_search |
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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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# BERT_large_with_preprocessing_grid_search |
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This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co./bert-large-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.0732 |
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- Precision: 0.0194 |
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- Recall: 0.125 |
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- F1: 0.0336 |
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- Accuracy: 0.1551 |
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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: 3e-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: 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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 2.1235 | 1.0 | 510 | 2.0738 | 0.0284 | 0.125 | 0.0462 | 0.2268 | |
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| 2.1058 | 2.0 | 1020 | 2.0805 | 0.0194 | 0.125 | 0.0336 | 0.1551 | |
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| 2.1039 | 3.0 | 1530 | 2.0780 | 0.0345 | 0.125 | 0.0541 | 0.2759 | |
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| 2.1045 | 4.0 | 2040 | 2.0734 | 0.0284 | 0.125 | 0.0462 | 0.2268 | |
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| 2.0963 | 5.0 | 2550 | 2.0779 | 0.0041 | 0.125 | 0.0080 | 0.0329 | |
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| 2.0975 | 6.0 | 3060 | 2.0750 | 0.0284 | 0.125 | 0.0462 | 0.2268 | |
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| 2.0944 | 7.0 | 3570 | 2.0734 | 0.0194 | 0.125 | 0.0336 | 0.1551 | |
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| 2.1004 | 8.0 | 4080 | 2.0820 | 0.0029 | 0.125 | 0.0056 | 0.0231 | |
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| 2.0974 | 9.0 | 4590 | 2.0724 | 0.0187 | 0.125 | 0.0326 | 0.1497 | |
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| 2.0936 | 10.0 | 5100 | 2.0732 | 0.0194 | 0.125 | 0.0336 | 0.1551 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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