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XLNet-Reddit-Sentiment-Analysis

Text Classification
Transformers
PyTorch
xlnet
Generated from Trainer
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End of training

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  1. README.md +9 -14
  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: 0.6345
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- - Rmse: 0.7328
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- - Accuracy: 0.733
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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: 10
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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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- | 0.7863 | 1.0 | 1000 | 0.6960 | 0.7436 | 0.732 |
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- | 0.679 | 2.0 | 2000 | 0.6345 | 0.7328 | 0.733 |
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- | 0.5893 | 3.0 | 3000 | 0.7480 | 0.7050 | 0.731 |
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- | 0.4862 | 4.0 | 4000 | 0.7551 | 0.6856 | 0.749 |
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- | 0.4068 | 5.0 | 5000 | 0.8476 | 0.6419 | 0.75 |
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- | 0.3396 | 6.0 | 6000 | 1.1664 | 0.6557 | 0.747 |
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- | 0.2717 | 7.0 | 7000 | 1.2858 | 0.6580 | 0.738 |
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- | 0.2173 | 8.0 | 8000 | 1.4618 | 0.6738 | 0.732 |
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- | 0.1828 | 9.0 | 9000 | 1.5711 | 0.6686 | 0.739 |
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- | 0.1587 | 10.0 | 10000 | 1.6188 | 0.6633 | 0.737 |
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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: 0.7753
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+ - Rmse: 0.6809
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+ - Accuracy: 0.8342
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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: 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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+ | 0.8876 | 1.0 | 3790 | 0.8646 | 0.6723 | 0.8332 |
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+ | 0.7213 | 2.0 | 7580 | 0.7753 | 0.6809 | 0.8342 |
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+ | 0.6517 | 3.0 | 11370 | 0.8566 | 0.6217 | 0.8543 |
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+ | 0.6016 | 4.0 | 15160 | 0.9131 | 0.6450 | 0.8532 |
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+ | 0.5317 | 5.0 | 18950 | 0.7939 | 0.6174 | 0.8659 |
 
 
 
 
 
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  ### Framework versions
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