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End of training

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README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bobbyw/deberta-v3-large_faster_learning_v2](https://huggingface.co/bobbyw/deberta-v3-large_faster_learning_v2) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0854
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- - Accuracy: 0.0218
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- - F1: 0.0427
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- - Precision: 0.0218
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- - Recall: 1.0
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  - Learning Rate: 0.0
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  ## Model description
@@ -50,14 +50,16 @@ The following hyperparameters were used during training:
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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: 2
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Rate |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-----:|
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- | 0.1134 | 1.0 | 689 | 0.0857 | 0.0218 | 0.0427 | 0.0218 | 1.0 | 0.001 |
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- | 0.1078 | 2.0 | 1378 | 0.0854 | 0.0218 | 0.0427 | 0.0218 | 1.0 | 0.0 |
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [bobbyw/deberta-v3-large_faster_learning_v2](https://huggingface.co/bobbyw/deberta-v3-large_faster_learning_v2) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0786
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+ - Accuracy: 0.0179
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+ - F1: 0.0332
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+ - Precision: 0.0170
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+ - Recall: 0.7727
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  - Learning Rate: 0.0
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  ## Model description
 
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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: 4
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Rate |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|
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+ | 0.1014 | 1.0 | 689 | 0.0842 | 0.0218 | 0.0427 | 0.0218 | 1.0 | 0.0015 |
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+ | 0.0975 | 2.0 | 1378 | 0.0830 | 0.0188 | 0.0370 | 0.0189 | 0.8636 | 0.001 |
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+ | 0.0973 | 3.0 | 2067 | 0.0764 | 0.0198 | 0.0389 | 0.0199 | 0.9091 | 0.0005 |
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+ | 0.0884 | 4.0 | 2756 | 0.0786 | 0.0179 | 0.0332 | 0.0170 | 0.7727 | 0.0 |
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  ### Framework versions
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