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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_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_with_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: 0.8911 |
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- Precision: 0.8371 |
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- Recall: 0.8239 |
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- F1: 0.8296 |
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- Accuracy: 0.8665 |
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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: 5e-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 | 255 | 0.6320 | 0.7746 | 0.8197 | 0.7918 | 0.8360 | |
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| 0.7073 | 2.0 | 510 | 0.6156 | 0.7967 | 0.8232 | 0.8055 | 0.8473 | |
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| 0.7073 | 3.0 | 765 | 0.6028 | 0.8104 | 0.8381 | 0.8201 | 0.8552 | |
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| 0.2389 | 4.0 | 1020 | 0.6896 | 0.8296 | 0.8296 | 0.8290 | 0.8655 | |
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| 0.2389 | 5.0 | 1275 | 0.7462 | 0.8279 | 0.8353 | 0.8310 | 0.8694 | |
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| 0.1264 | 6.0 | 1530 | 0.9275 | 0.8488 | 0.8112 | 0.8271 | 0.8684 | |
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| 0.1264 | 7.0 | 1785 | 0.8244 | 0.8393 | 0.8313 | 0.8347 | 0.8729 | |
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| 0.0851 | 8.0 | 2040 | 0.8776 | 0.8281 | 0.8226 | 0.8249 | 0.8655 | |
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| 0.0851 | 9.0 | 2295 | 0.8838 | 0.8440 | 0.8278 | 0.8346 | 0.8675 | |
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| 0.0546 | 10.0 | 2550 | 0.8911 | 0.8371 | 0.8239 | 0.8296 | 0.8665 | |
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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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