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README.md CHANGED
@@ -18,14 +18,14 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3452
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- - F1 Macro: 0.9122
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- - F1: 0.9423
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- - F1 Neg: 0.8821
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  - Acc: 0.9225
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- - Prec: 0.9440
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- - Recall: 0.9405
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- - Mcc: 0.8244
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  ## Model description
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@@ -51,22 +51,16 @@ The following hyperparameters were used during training:
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  - distributed_type: multi-GPU
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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: 9
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  - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 | F1 Neg | Acc | Prec | Recall | Mcc |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|:------:|:------:|
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- | No log | 1.0 | 412 | 0.2874 | 0.8817 | 0.9175 | 0.8459 | 0.8925 | 0.9019 | 0.9336 | 0.7644 |
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- | 0.4079 | 2.0 | 824 | 0.3926 | 0.8937 | 0.9243 | 0.8632 | 0.9025 | 0.9189 | 0.9297 | 0.7875 |
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- | 0.2262 | 3.0 | 1236 | 0.4043 | 0.9135 | 0.9373 | 0.8897 | 0.92 | 0.9409 | 0.9336 | 0.8270 |
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- | 0.1144 | 4.0 | 1648 | 0.4935 | 0.9055 | 0.9312 | 0.8797 | 0.9125 | 0.9368 | 0.9258 | 0.8111 |
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- | 0.0444 | 5.0 | 2060 | 0.6089 | 0.9063 | 0.9304 | 0.8822 | 0.9125 | 0.9474 | 0.9141 | 0.8136 |
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- | 0.0444 | 6.0 | 2472 | 0.6717 | 0.9063 | 0.9304 | 0.8822 | 0.9125 | 0.9474 | 0.9141 | 0.8136 |
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- | 0.0211 | 7.0 | 2884 | 0.7189 | 0.8963 | 0.9264 | 0.8662 | 0.905 | 0.9192 | 0.9336 | 0.7928 |
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- | 0.0127 | 8.0 | 3296 | 0.7510 | 0.8988 | 0.9284 | 0.8693 | 0.9075 | 0.9195 | 0.9375 | 0.7980 |
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- | 0.0025 | 9.0 | 3708 | 0.7730 | 0.9058 | 0.9310 | 0.8805 | 0.9125 | 0.9402 | 0.9219 | 0.8118 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3280
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+ - F1 Macro: 0.9125
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+ - F1: 0.9421
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+ - F1 Neg: 0.8830
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  - Acc: 0.9225
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+ - Prec: 0.9474
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+ - Recall: 0.9368
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+ - Mcc: 0.8252
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  ## Model description
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  - distributed_type: multi-GPU
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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: 3
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  - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 | F1 Neg | Acc | Prec | Recall | Mcc |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|:------:|:------:|
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+ | 0.2495 | 1.0 | 1647 | 0.3554 | 0.9111 | 0.9349 | 0.8874 | 0.9175 | 0.9442 | 0.9258 | 0.8226 |
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+ | 0.091 | 2.0 | 3294 | 0.5621 | 0.9011 | 0.9308 | 0.8714 | 0.91 | 0.9167 | 0.9453 | 0.8031 |
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+ | 0.0202 | 3.0 | 4941 | 0.6612 | 0.9049 | 0.9318 | 0.8780 | 0.9125 | 0.9300 | 0.9336 | 0.8098 |
 
 
 
 
 
 
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  ### Framework versions
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