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djsull/aha_class

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README.md CHANGED
@@ -1,5 +1,5 @@
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  ---
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- base_model: klue/roberta-small
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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
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- This model is a fine-tuned version of [klue/roberta-small](https://huggingface.co/klue/roberta-small) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0762
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- - F1: 0.9705
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- - Roc Auc: 0.9766
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- - Accuracy: 0.9565
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  ## Model description
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@@ -51,20 +51,19 @@ The following hyperparameters were used during training:
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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 | 0.1926 | 0.9218 | 0.9440 | 0.8609 |
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- | No log | 2.0 | 84 | 0.1140 | 0.9580 | 0.9679 | 0.9304 |
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- | No log | 3.0 | 126 | 0.1016 | 0.9536 | 0.9637 | 0.9217 |
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- | No log | 4.0 | 168 | 0.0800 | 0.9705 | 0.9766 | 0.9478 |
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- | No log | 5.0 | 210 | 0.0800 | 0.9661 | 0.9724 | 0.9478 |
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- | No log | 6.0 | 252 | 0.0817 | 0.9620 | 0.9701 | 0.9391 |
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- | No log | 7.0 | 294 | 0.0788 | 0.9661 | 0.9724 | 0.9478 |
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- | No log | 8.0 | 336 | 0.0803 | 0.9705 | 0.9766 | 0.9565 |
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- | No log | 9.0 | 378 | 0.0762 | 0.9705 | 0.9766 | 0.9565 |
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- | No log | 10.0 | 420 | 0.0837 | 0.9664 | 0.9743 | 0.9478 |
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- | No log | 11.0 | 462 | 0.0800 | 0.9664 | 0.9743 | 0.9478 |
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- | 0.0807 | 12.0 | 504 | 0.0815 | 0.9664 | 0.9743 | 0.9478 |
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- | 0.0807 | 13.0 | 546 | 0.0808 | 0.9664 | 0.9743 | 0.9478 |
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- | 0.0807 | 14.0 | 588 | 0.0816 | 0.9664 | 0.9743 | 0.9478 |
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  ### Framework versions
 
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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:
 
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  # aha_class
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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: 0.0761
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+ - F1: 0.9748
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+ - Roc Auc: 0.9808
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+ - Accuracy: 0.9652
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  ## Model description
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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 | 0.3253 | 0.8814 | 0.9082 | 0.8435 |
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+ | No log | 2.0 | 84 | 0.1631 | 0.9661 | 0.9724 | 0.9478 |
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+ | No log | 3.0 | 126 | 0.1213 | 0.9661 | 0.9724 | 0.9478 |
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+ | No log | 4.0 | 168 | 0.0921 | 0.9705 | 0.9766 | 0.9565 |
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+ | No log | 5.0 | 210 | 0.0869 | 0.9705 | 0.9766 | 0.9565 |
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+ | No log | 6.0 | 252 | 0.0868 | 0.9748 | 0.9808 | 0.9652 |
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+ | No log | 7.0 | 294 | 0.0825 | 0.9746 | 0.9788 | 0.9652 |
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+ | No log | 8.0 | 336 | 0.0761 | 0.9748 | 0.9808 | 0.9652 |
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+ | No log | 9.0 | 378 | 0.0820 | 0.9707 | 0.9785 | 0.9565 |
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+ | No log | 10.0 | 420 | 0.0774 | 0.9748 | 0.9808 | 0.9652 |
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+ | No log | 11.0 | 462 | 0.0772 | 0.9707 | 0.9785 | 0.9565 |
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+ | 0.1111 | 12.0 | 504 | 0.0767 | 0.9748 | 0.9808 | 0.9652 |
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+ | 0.1111 | 13.0 | 546 | 0.0785 | 0.9748 | 0.9808 | 0.9652 |
 
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  ### Framework versions
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@@ -1,14 +1,16 @@
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