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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- filter_v2 |
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metrics: |
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- f1 |
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- accuracy |
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model-index: |
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- name: favs_filter_classification_v2 |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: filter_v2 |
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type: filter_v2 |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: F1 |
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type: f1 |
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value: 0.9666666666666667 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9375 |
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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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# favs_filter_classification_v2 |
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the filter_v2 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2721 |
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- F1: 0.9667 |
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- Roc Auc: 0.9772 |
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- Accuracy: 0.9375 |
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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: 1.5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| |
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| 0.7591 | 1.0 | 14 | 0.6660 | 0.3137 | 0.5541 | 0.0 | |
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| 0.6506 | 2.0 | 28 | 0.5575 | 0.4706 | 0.6451 | 0.0625 | |
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| 0.5006 | 3.0 | 42 | 0.5010 | 0.5385 | 0.6846 | 0.0625 | |
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| 0.4416 | 4.0 | 56 | 0.4536 | 0.6538 | 0.7528 | 0.125 | |
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| 0.3815 | 5.0 | 70 | 0.4127 | 0.8070 | 0.8589 | 0.5 | |
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| 0.3468 | 6.0 | 84 | 0.3748 | 0.8621 | 0.8984 | 0.5625 | |
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| 0.3316 | 7.0 | 98 | 0.3487 | 0.8621 | 0.8984 | 0.5625 | |
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| 0.2834 | 8.0 | 112 | 0.3191 | 0.9 | 0.9317 | 0.6875 | |
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| 0.2565 | 9.0 | 126 | 0.2970 | 0.9492 | 0.9606 | 0.875 | |
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| 0.2241 | 10.0 | 140 | 0.2721 | 0.9667 | 0.9772 | 0.9375 | |
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| 0.214 | 11.0 | 154 | 0.2563 | 0.9492 | 0.9606 | 0.875 | |
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| 0.2041 | 12.0 | 168 | 0.2499 | 0.9492 | 0.9606 | 0.875 | |
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| 0.1831 | 13.0 | 182 | 0.2353 | 0.9492 | 0.9606 | 0.875 | |
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| 0.1852 | 14.0 | 196 | 0.2285 | 0.9492 | 0.9606 | 0.875 | |
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| 0.1636 | 15.0 | 210 | 0.2178 | 0.9667 | 0.9772 | 0.9375 | |
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| 0.1581 | 16.0 | 224 | 0.2110 | 0.9667 | 0.9772 | 0.9375 | |
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| 0.1473 | 17.0 | 238 | 0.2057 | 0.9492 | 0.9606 | 0.875 | |
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| 0.1479 | 18.0 | 252 | 0.2025 | 0.9667 | 0.9772 | 0.9375 | |
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| 0.141 | 19.0 | 266 | 0.2038 | 0.9667 | 0.9772 | 0.9375 | |
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| 0.1424 | 20.0 | 280 | 0.2032 | 0.9667 | 0.9772 | 0.9375 | |
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### Framework versions |
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- Transformers 4.21.1 |
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- Pytorch 1.12.1 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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