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End of training

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  1. README.md +14 -14
  2. pytorch_model.bin +1 -1
README.md CHANGED
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  ---
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  license: mit
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- base_model: xlnet-base-cased
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  tags:
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  - generated_from_trainer
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  model-index:
@@ -13,10 +13,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # Sentiment-Analysis-Model
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- This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7202
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- - F1 Score: 0.6921
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  ## Model description
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@@ -47,16 +47,16 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | F1 Score |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.8571 | 0.5 | 500 | 0.7520 | 0.6771 |
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- | 0.7848 | 1.0 | 1000 | 0.7468 | 0.6780 |
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- | 0.8367 | 1.5 | 1500 | 0.8781 | 0.5579 |
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- | 0.8949 | 2.0 | 2000 | 0.8666 | 0.5704 |
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- | 0.7922 | 2.5 | 2500 | 0.7379 | 0.6738 |
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- | 0.748 | 3.0 | 3000 | 0.7218 | 0.6833 |
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- | 0.7604 | 3.5 | 3500 | 0.7853 | 0.6645 |
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- | 0.7704 | 4.0 | 4000 | 0.7281 | 0.6867 |
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- | 0.7562 | 4.5 | 4500 | 0.7265 | 0.6904 |
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- | 0.7195 | 5.0 | 5000 | 0.7202 | 0.6921 |
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  ### Framework versions
 
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  ---
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  license: mit
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+ base_model: roberta-base
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  tags:
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  - generated_from_trainer
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  model-index:
 
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  # Sentiment-Analysis-Model
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+ This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6488
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+ - F1 Score: 0.7281
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | F1 Score |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.8011 | 0.5 | 500 | 0.8189 | 0.6563 |
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+ | 0.7437 | 1.0 | 1000 | 0.7877 | 0.6793 |
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+ | 0.6996 | 1.5 | 1500 | 0.6979 | 0.6996 |
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+ | 0.6886 | 2.0 | 2000 | 0.6893 | 0.6910 |
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+ | 0.6384 | 2.5 | 2500 | 0.8285 | 0.7133 |
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+ | 0.6254 | 3.0 | 3000 | 0.6488 | 0.7281 |
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+ | 0.56 | 3.5 | 3500 | 0.6755 | 0.7402 |
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+ | 0.5731 | 4.0 | 4000 | 0.6775 | 0.7456 |
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+ | 0.504 | 4.5 | 4500 | 0.7232 | 0.7407 |
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+ | 0.4839 | 5.0 | 5000 | 0.7219 | 0.7512 |
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  ### Framework versions
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