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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: 1.0 |
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- name: Accuracy |
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type: accuracy |
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value: 1.0 |
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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: 0.2580 |
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- F1: 1.0 |
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- Roc Auc: 1.0 |
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- Accuracy: 1.0 |
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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: 15 |
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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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| 0.6752 | 1.0 | 13 | 0.6166 | 0.3810 | 0.5772 | 0.0 | |
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| 0.5905 | 2.0 | 26 | 0.5326 | 0.6286 | 0.7399 | 0.3636 | |
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| 0.5004 | 3.0 | 39 | 0.4812 | 0.5 | 0.6636 | 0.2727 | |
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| 0.4268 | 4.0 | 52 | 0.4346 | 0.7027 | 0.7899 | 0.4545 | |
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| 0.391 | 5.0 | 65 | 0.4072 | 0.8205 | 0.8737 | 0.5455 | |
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| 0.3725 | 6.0 | 78 | 0.3666 | 0.8108 | 0.8575 | 0.6364 | |
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| 0.3215 | 7.0 | 91 | 0.3382 | 0.8889 | 0.9 | 0.7273 | |
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| 0.3094 | 8.0 | 104 | 0.3083 | 0.9474 | 0.95 | 0.8182 | |
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| 0.2825 | 9.0 | 117 | 0.2925 | 0.9189 | 0.925 | 0.7273 | |
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| 0.2596 | 10.0 | 130 | 0.2801 | 0.9474 | 0.95 | 0.8182 | |
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| 0.2517 | 11.0 | 143 | 0.2580 | 1.0 | 1.0 | 1.0 | |
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| 0.2308 | 12.0 | 156 | 0.2538 | 0.9744 | 0.975 | 0.9091 | |
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| 0.238 | 13.0 | 169 | 0.2459 | 0.9744 | 0.975 | 0.9091 | |
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| 0.2194 | 14.0 | 182 | 0.2379 | 1.0 | 1.0 | 1.0 | |
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| 0.2181 | 15.0 | 195 | 0.2366 | 1.0 | 1.0 | 1.0 | |
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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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