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README.md CHANGED
@@ -16,9 +16,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.5272
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- - Icm: 0.2161
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- - Icmnorm: 0.6098
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- - Fmeasure: 0.7394
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  ## Model description
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@@ -44,16 +44,22 @@ 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: 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 | Icm | Icmnorm | Fmeasure |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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- | No log | 1.0 | 193 | 0.5272 | 0.2161 | 0.6098 | 0.7394 |
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- | No log | 2.0 | 386 | 0.6158 | 0.0402 | 0.5204 | 0.6763 |
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- | 0.5577 | 3.0 | 579 | 0.6748 | 0.1302 | 0.5661 | 0.7128 |
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.5272
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+ - Icm: 0.2125
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+ - Icmnorm: 0.6079
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+ - Fmeasure: 0.7412
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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: 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 | Icm | Icmnorm | Fmeasure |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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+ | No log | 1.0 | 193 | 0.5272 | 0.2125 | 0.6079 | 0.7412 |
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+ | No log | 2.0 | 386 | 0.5666 | 0.1794 | 0.5911 | 0.7232 |
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+ | 0.5355 | 3.0 | 579 | 0.5858 | 0.2074 | 0.6054 | 0.7394 |
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+ | 0.5355 | 4.0 | 772 | 0.9107 | 0.0682 | 0.5346 | 0.6930 |
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+ | 0.5355 | 5.0 | 965 | 1.4701 | 0.0555 | 0.5282 | 0.6870 |
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+ | 0.2599 | 6.0 | 1158 | 1.5765 | 0.1378 | 0.5700 | 0.7162 |
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+ | 0.2599 | 7.0 | 1351 | 1.8163 | 0.1302 | 0.5661 | 0.7128 |
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+ | 0.1043 | 8.0 | 1544 | 1.8608 | 0.1134 | 0.5576 | 0.7074 |
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+ | 0.1043 | 9.0 | 1737 | 1.8539 | 0.1403 | 0.5713 | 0.7171 |
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  ### Framework versions
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