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djsull/aha_class_v1

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README.md CHANGED
@@ -1,5 +1,5 @@
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  ---
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- base_model: monologg/kobigbird-bert-base
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  tags:
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  - generated_from_trainer
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  metrics:
@@ -15,12 +15,12 @@ should probably proofread and complete it, then remove this comment. -->
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  # aha_class_v1
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- This model is a fine-tuned version of [monologg/kobigbird-bert-base](https://huggingface.co/monologg/kobigbird-bert-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0796
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- - F1: 0.9623
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- - Roc Auc: 0.9721
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- - Accuracy: 0.9478
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  ## Model description
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@@ -49,21 +49,23 @@ The following hyperparameters were used during training:
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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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- | No log | 1.0 | 42 | 0.3116 | 0.9256 | 0.9463 | 0.8870 |
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- | No log | 2.0 | 84 | 0.1718 | 0.9746 | 0.9788 | 0.9565 |
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- | No log | 3.0 | 126 | 0.1375 | 0.9576 | 0.9659 | 0.9391 |
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- | No log | 4.0 | 168 | 0.1007 | 0.9702 | 0.9746 | 0.9565 |
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- | No log | 5.0 | 210 | 0.0927 | 0.9617 | 0.9682 | 0.9478 |
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- | No log | 6.0 | 252 | 0.0927 | 0.9617 | 0.9682 | 0.9478 |
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- | No log | 7.0 | 294 | 0.0910 | 0.9617 | 0.9682 | 0.9478 |
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- | No log | 8.0 | 336 | 0.0796 | 0.9623 | 0.9721 | 0.9478 |
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- | No log | 9.0 | 378 | 0.0953 | 0.9580 | 0.9679 | 0.9391 |
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- | No log | 10.0 | 420 | 0.0796 | 0.9661 | 0.9724 | 0.9565 |
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- | No log | 11.0 | 462 | 0.0890 | 0.9580 | 0.9679 | 0.9391 |
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- | 0.1161 | 12.0 | 504 | 0.0910 | 0.9580 | 0.9679 | 0.9391 |
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- | 0.1161 | 13.0 | 546 | 0.0916 | 0.9580 | 0.9679 | 0.9391 |
 
 
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  ### Framework versions
 
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  ---
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+ base_model: klue/roberta-base
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  # aha_class_v1
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+ This model is a fine-tuned version of [klue/roberta-base](https://huggingface.co/klue/roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0020
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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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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---:|:-------:|:--------:|
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+ | No log | 1.0 | 35 | 0.0594 | 1.0 | 1.0 | 1.0 |
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+ | No log | 2.0 | 70 | 0.0186 | 1.0 | 1.0 | 1.0 |
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+ | No log | 3.0 | 105 | 0.0108 | 1.0 | 1.0 | 1.0 |
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+ | No log | 4.0 | 140 | 0.0075 | 1.0 | 1.0 | 1.0 |
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+ | No log | 5.0 | 175 | 0.0057 | 1.0 | 1.0 | 1.0 |
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+ | No log | 6.0 | 210 | 0.0044 | 1.0 | 1.0 | 1.0 |
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+ | No log | 7.0 | 245 | 0.0036 | 1.0 | 1.0 | 1.0 |
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+ | No log | 8.0 | 280 | 0.0031 | 1.0 | 1.0 | 1.0 |
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+ | No log | 9.0 | 315 | 0.0027 | 1.0 | 1.0 | 1.0 |
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+ | No log | 10.0 | 350 | 0.0025 | 1.0 | 1.0 | 1.0 |
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+ | No log | 11.0 | 385 | 0.0023 | 1.0 | 1.0 | 1.0 |
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+ | No log | 12.0 | 420 | 0.0021 | 1.0 | 1.0 | 1.0 |
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+ | No log | 13.0 | 455 | 0.0020 | 1.0 | 1.0 | 1.0 |
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+ | No log | 14.0 | 490 | 0.0020 | 1.0 | 1.0 | 1.0 |
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+ | 0.0393 | 15.0 | 525 | 0.0020 | 1.0 | 1.0 | 1.0 |
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  ### Framework versions
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