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End of training

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  1. README.md +11 -9
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -17,9 +17,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7135
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- - Rmse: 0.6123
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- - Accuracy: 0.8691
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  ## Model description
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@@ -44,17 +44,19 @@ 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: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Rmse | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:------:|:--------:|
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- | 0.8907 | 1.0 | 3790 | 0.9401 | 0.6715 | 0.8152 |
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- | 0.7855 | 2.0 | 7580 | 0.7974 | 0.6301 | 0.8501 |
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- | 0.6837 | 3.0 | 11370 | 0.8520 | 0.6384 | 0.8553 |
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- | 0.6271 | 4.0 | 15160 | 0.7731 | 0.6140 | 0.8669 |
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- | 0.5311 | 5.0 | 18950 | 0.7135 | 0.6123 | 0.8691 |
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.7042
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+ - Rmse: 0.6062
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+ - Accuracy: 0.8574
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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: 7
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Rmse | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:------:|:--------:|
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+ | 0.8318 | 1.0 | 3790 | 0.7042 | 0.6062 | 0.8574 |
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+ | 0.6979 | 2.0 | 7580 | 0.8326 | 0.6754 | 0.8416 |
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+ | 0.7497 | 3.0 | 11370 | 1.0764 | 0.7446 | 0.8004 |
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+ | 0.8444 | 4.0 | 15160 | 0.9529 | 0.6628 | 0.8458 |
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+ | 0.6879 | 5.0 | 18950 | 0.8014 | 0.6442 | 0.8479 |
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+ | 0.5306 | 6.0 | 22740 | 0.7252 | 0.6174 | 0.8627 |
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+ | 0.466 | 7.0 | 26530 | 0.7364 | 0.5965 | 0.8691 |
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  ### Framework versions
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