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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: 1.0365 |
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- Precision: 0.8410 |
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- Recall: 0.8308 |
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- F1: 0.8352 |
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- Accuracy: 0.8753 |
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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: 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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| 0.9616 | 1.0 | 510 | 0.6482 | 0.7704 | 0.8009 | 0.7781 | 0.8360 | |
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| 0.4395 | 2.0 | 1020 | 0.7507 | 0.8422 | 0.7993 | 0.8157 | 0.8552 | |
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| 0.2995 | 3.0 | 1530 | 0.7064 | 0.8445 | 0.8213 | 0.8287 | 0.8684 | |
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| 0.2117 | 4.0 | 2040 | 0.7889 | 0.8262 | 0.8325 | 0.8245 | 0.8679 | |
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| 0.1805 | 5.0 | 2550 | 0.9295 | 0.8406 | 0.8161 | 0.8271 | 0.8670 | |
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| 0.1225 | 6.0 | 3060 | 0.9491 | 0.8429 | 0.8260 | 0.8333 | 0.8758 | |
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| 0.0983 | 7.0 | 3570 | 0.9901 | 0.8444 | 0.8299 | 0.8359 | 0.8773 | |
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| 0.0869 | 8.0 | 4080 | 1.0300 | 0.8377 | 0.8278 | 0.8319 | 0.8719 | |
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| 0.0745 | 9.0 | 4590 | 1.0220 | 0.8439 | 0.8341 | 0.8379 | 0.8773 | |
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| 0.0591 | 10.0 | 5100 | 1.0365 | 0.8410 | 0.8308 | 0.8352 | 0.8753 | |
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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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