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End of training

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README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [dadashzadeh/tiny-bert-Sentiment-persian](https://huggingface.co/dadashzadeh/tiny-bert-Sentiment-persian) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6538
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- - Accuracy: 0.7287
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  ## Model description
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@@ -38,39 +38,23 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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- - train_batch_size: 12
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- - eval_batch_size: 12
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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: 22
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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- |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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- | 0.8279 | 1.0 | 2384 | 0.7849 | 0.6544 |
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- | 0.8218 | 2.0 | 4768 | 0.7674 | 0.6587 |
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- | 0.8155 | 3.0 | 7152 | 0.7421 | 0.6821 |
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- | 0.8037 | 4.0 | 9536 | 0.7378 | 0.6829 |
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- | 0.799 | 5.0 | 11920 | 0.7983 | 0.6324 |
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- | 0.7943 | 6.0 | 14304 | 0.7071 | 0.7015 |
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- | 0.7764 | 7.0 | 16688 | 0.7438 | 0.6756 |
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- | 0.7763 | 8.0 | 19072 | 0.7328 | 0.6829 |
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- | 0.7717 | 9.0 | 21456 | 0.7300 | 0.6825 |
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- | 0.7733 | 10.0 | 23840 | 0.6943 | 0.7106 |
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- | 0.7517 | 11.0 | 26224 | 0.6859 | 0.7210 |
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- | 0.7515 | 12.0 | 28608 | 0.6538 | 0.7287 |
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- | 0.7497 | 13.0 | 30992 | 0.6930 | 0.7084 |
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- | 0.7177 | 14.0 | 33376 | 0.7055 | 0.6972 |
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- | 0.734 | 15.0 | 35760 | 0.6893 | 0.7123 |
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- | 0.7247 | 16.0 | 38144 | 0.7026 | 0.7045 |
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- | 0.7317 | 17.0 | 40528 | 0.6711 | 0.7210 |
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- | 0.7145 | 18.0 | 42912 | 0.7192 | 0.6911 |
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- | 0.7136 | 19.0 | 45296 | 0.6951 | 0.7102 |
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- | 0.7159 | 20.0 | 47680 | 0.6776 | 0.7197 |
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- | 0.7278 | 21.0 | 50064 | 0.6814 | 0.7162 |
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- | 0.6952 | 22.0 | 52448 | 0.6829 | 0.7158 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [dadashzadeh/tiny-bert-Sentiment-persian](https://huggingface.co/dadashzadeh/tiny-bert-Sentiment-persian) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6672
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+ - Accuracy: 0.7279
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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+ - train_batch_size: 20
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+ - eval_batch_size: 20
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+ - seed: 10
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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: 6
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.696 | 1.0 | 1431 | 0.6928 | 0.7136 |
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+ | 0.6826 | 2.0 | 2862 | 0.6893 | 0.7153 |
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+ | 0.6737 | 3.0 | 4293 | 0.6620 | 0.7257 |
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+ | 0.6801 | 4.0 | 5724 | 0.6579 | 0.7317 |
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+ | 0.6682 | 5.0 | 7155 | 0.6662 | 0.7270 |
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+ | 0.6756 | 6.0 | 8586 | 0.6672 | 0.7279 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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