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--- |
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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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- f1 |
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- accuracy |
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model-index: |
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- name: BERT_without_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_without_preprocessing_grid_search |
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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: 0.6213 |
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- Precision: 0.8399 |
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- Recall: 0.8622 |
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- F1: 0.8498 |
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- Accuracy: 0.8798 |
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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: 32 |
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- eval_batch_size: 32 |
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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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| No log | 1.0 | 257 | 0.6305 | 0.7254 | 0.8018 | 0.7512 | 0.8180 | |
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| 0.8689 | 2.0 | 514 | 0.4877 | 0.8120 | 0.8500 | 0.8245 | 0.8667 | |
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| 0.8689 | 3.0 | 771 | 0.4490 | 0.7911 | 0.8590 | 0.8148 | 0.8599 | |
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| 0.2702 | 4.0 | 1028 | 0.4748 | 0.8291 | 0.8689 | 0.8457 | 0.8730 | |
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| 0.2702 | 5.0 | 1285 | 0.5217 | 0.8326 | 0.8543 | 0.8413 | 0.8783 | |
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| 0.1505 | 6.0 | 1542 | 0.5288 | 0.8351 | 0.8650 | 0.8481 | 0.8754 | |
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| 0.1505 | 7.0 | 1799 | 0.5801 | 0.8417 | 0.8585 | 0.8487 | 0.8769 | |
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| 0.092 | 8.0 | 2056 | 0.5721 | 0.8402 | 0.8694 | 0.8535 | 0.8818 | |
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| 0.092 | 9.0 | 2313 | 0.6135 | 0.8453 | 0.8618 | 0.8522 | 0.8808 | |
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| 0.0723 | 10.0 | 2570 | 0.6213 | 0.8399 | 0.8622 | 0.8498 | 0.8798 | |
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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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