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nguyenkhoa2407
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favs_filter_classification_v2

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Eval Results
Inference Endpoints
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update model card README.md

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@@ -35,7 +35,7 @@ should probably proofread and complete it, then remove this comment. -->
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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
@@ -57,33 +57,38 @@ More information needed
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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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  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: 0.2201
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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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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 1.3e-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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+ | 0.6747 | 1.0 | 13 | 0.5868 | 0.5 | 0.6649 | 0.1818 |
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+ | 0.5843 | 2.0 | 26 | 0.5321 | 0.4828 | 0.6575 | 0.0 |
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+ | 0.5445 | 3.0 | 39 | 0.5029 | 0.6 | 0.7162 | 0.2727 |
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+ | 0.4713 | 4.0 | 52 | 0.4667 | 0.6207 | 0.725 | 0.2727 |
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+ | 0.4304 | 5.0 | 65 | 0.4321 | 0.6667 | 0.7575 | 0.4545 |
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+ | 0.3983 | 6.0 | 78 | 0.3909 | 0.7500 | 0.8 | 0.4545 |
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+ | 0.3433 | 7.0 | 91 | 0.3571 | 0.7879 | 0.825 | 0.5455 |
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+ | 0.3186 | 8.0 | 104 | 0.3319 | 0.8235 | 0.85 | 0.6364 |
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+ | 0.2967 | 9.0 | 117 | 0.3049 | 0.8571 | 0.875 | 0.6364 |
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+ | 0.2739 | 10.0 | 130 | 0.2857 | 0.8571 | 0.875 | 0.6364 |
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+ | 0.2535 | 11.0 | 143 | 0.2686 | 0.9474 | 0.95 | 0.8182 |
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+ | 0.234 | 12.0 | 156 | 0.2501 | 0.9474 | 0.95 | 0.8182 |
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+ | 0.2338 | 13.0 | 169 | 0.2358 | 0.9474 | 0.95 | 0.8182 |
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+ | 0.2049 | 14.0 | 182 | 0.2201 | 1.0 | 1.0 | 1.0 |
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+ | 0.1942 | 15.0 | 195 | 0.2098 | 1.0 | 1.0 | 1.0 |
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+ | 0.1957 | 16.0 | 208 | 0.2063 | 1.0 | 1.0 | 1.0 |
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+ | 0.1892 | 17.0 | 221 | 0.1969 | 1.0 | 1.0 | 1.0 |
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+ | 0.1836 | 18.0 | 234 | 0.1919 | 1.0 | 1.0 | 1.0 |
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+ | 0.1767 | 19.0 | 247 | 0.1909 | 1.0 | 1.0 | 1.0 |
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+ | 0.1702 | 20.0 | 260 | 0.1901 | 1.0 | 1.0 | 1.0 |
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  ### Framework versions