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HerbertAIHug
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NLP_Capstone

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
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  1. README.md +29 -30
  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: roberta-base
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  tags:
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  - generated_from_trainer
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  metrics:
@@ -15,10 +14,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # NLP_Capstone
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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: 0.3184
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- - Accuracy: 0.9131
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  ## Model description
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@@ -37,7 +36,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 5e-05
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
@@ -49,30 +48,30 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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- | 0.4675 | 0.2 | 500 | 0.3681 | 0.8803 |
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- | 0.3759 | 0.4 | 1000 | 0.5198 | 0.8721 |
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- | 0.3657 | 0.6 | 1500 | 0.3482 | 0.9040 |
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- | 0.3139 | 0.8 | 2000 | 0.3184 | 0.9131 |
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- | 0.3442 | 1.0 | 2500 | 0.3415 | 0.9058 |
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- | 0.2745 | 1.2 | 3000 | 0.3522 | 0.8745 |
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- | 0.2413 | 1.41 | 3500 | 0.3306 | 0.9105 |
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- | 0.2517 | 1.61 | 4000 | 0.3334 | 0.9243 |
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- | 0.2499 | 1.81 | 4500 | 0.3907 | 0.9072 |
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- | 0.2473 | 2.01 | 5000 | 0.3441 | 0.9229 |
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- | 0.1608 | 2.21 | 5500 | 0.3697 | 0.9187 |
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- | 0.173 | 2.41 | 6000 | 0.3362 | 0.9225 |
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- | 0.1749 | 2.61 | 6500 | 0.3591 | 0.9237 |
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- | 0.1725 | 2.81 | 7000 | 0.4014 | 0.9255 |
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- | 0.1616 | 3.01 | 7500 | 0.3456 | 0.9271 |
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- | 0.1047 | 3.21 | 8000 | 0.3773 | 0.9285 |
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- | 0.1062 | 3.41 | 8500 | 0.3980 | 0.9217 |
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- | 0.1029 | 3.61 | 9000 | 0.3808 | 0.9293 |
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- | 0.1004 | 3.81 | 9500 | 0.3696 | 0.9289 |
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- | 0.0822 | 4.01 | 10000 | 0.3950 | 0.9309 |
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- | 0.0408 | 4.22 | 10500 | 0.4388 | 0.9285 |
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- | 0.0643 | 4.42 | 11000 | 0.4204 | 0.9285 |
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- | 0.0536 | 4.62 | 11500 | 0.4102 | 0.9301 |
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- | 0.0508 | 4.82 | 12000 | 0.4139 | 0.9297 |
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  ### Framework versions
 
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  ---
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+ base_model: huawei-noah/TinyBERT_General_4L_312D
 
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  # NLP_Capstone
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+ This model is a fine-tuned version of [huawei-noah/TinyBERT_General_4L_312D](https://huggingface.co/huawei-noah/TinyBERT_General_4L_312D) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3176
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+ - Accuracy: 0.8671
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  ## Model description
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  ### Training hyperparameters
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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: 8
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  - eval_batch_size: 8
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 0.5286 | 0.2 | 500 | 0.4169 | 0.8251 |
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+ | 0.4299 | 0.4 | 1000 | 0.4137 | 0.8332 |
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+ | 0.3856 | 0.6 | 1500 | 0.3714 | 0.8512 |
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+ | 0.3692 | 0.8 | 2000 | 0.3176 | 0.8671 |
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+ | 0.3604 | 1.0 | 2500 | 0.3869 | 0.8635 |
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+ | 0.3457 | 1.2 | 3000 | 0.4126 | 0.8631 |
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+ | 0.3291 | 1.41 | 3500 | 0.4272 | 0.8675 |
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+ | 0.3481 | 1.61 | 4000 | 0.3754 | 0.8775 |
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+ | 0.3253 | 1.81 | 4500 | 0.4293 | 0.8649 |
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+ | 0.3306 | 2.01 | 5000 | 0.3807 | 0.8789 |
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+ | 0.2849 | 2.21 | 5500 | 0.4291 | 0.8803 |
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+ | 0.2824 | 2.41 | 6000 | 0.4058 | 0.8797 |
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+ | 0.279 | 2.61 | 6500 | 0.4521 | 0.8761 |
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+ | 0.2944 | 2.81 | 7000 | 0.4986 | 0.8747 |
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+ | 0.3347 | 3.01 | 7500 | 0.4364 | 0.8815 |
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+ | 0.2622 | 3.21 | 8000 | 0.5368 | 0.8703 |
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+ | 0.2494 | 3.41 | 8500 | 0.4795 | 0.8854 |
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+ | 0.2645 | 3.61 | 9000 | 0.4795 | 0.8864 |
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+ | 0.243 | 3.81 | 9500 | 0.4570 | 0.8874 |
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+ | 0.2399 | 4.01 | 10000 | 0.5219 | 0.8795 |
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+ | 0.2103 | 4.22 | 10500 | 0.5325 | 0.8775 |
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+ | 0.2196 | 4.42 | 11000 | 0.5629 | 0.8729 |
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+ | 0.2494 | 4.62 | 11500 | 0.5087 | 0.8826 |
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+ | 0.1968 | 4.82 | 12000 | 0.5332 | 0.8779 |
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  ### Framework versions
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