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bertweet-large-sexism-detector

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  2. model.safetensors +1 -1
README.md CHANGED
@@ -14,10 +14,10 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [NLP-LTU/bertweet-large-sexism-detector](https://huggingface.co/NLP-LTU/bertweet-large-sexism-detector) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.1313
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- - Icm: 0.1644
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- - Icmnorm: 0.5834
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- - Fmeasure: 0.7248
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  ## Model description
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@@ -36,31 +36,35 @@ 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: 1e-06
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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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  - 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: 6
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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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- | 0.8513 | 1.0 | 1625 | 0.9252 | 0.1119 | 0.5568 | 0.7073 |
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- | 0.872 | 2.0 | 3250 | 1.1313 | 0.1644 | 0.5834 | 0.7248 |
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- | 0.9077 | 3.0 | 4875 | 1.2531 | 0.1286 | 0.5653 | 0.7128 |
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- | 0.7907 | 4.0 | 6500 | 1.3570 | 0.1644 | 0.5834 | 0.7248 |
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- | 0.6587 | 5.0 | 8125 | 1.4076 | 0.1644 | 0.5834 | 0.7248 |
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- | 0.6787 | 6.0 | 9750 | 1.4216 | 0.1644 | 0.5834 | 0.7248 |
 
 
 
 
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  ### Framework versions
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- - Transformers 4.39.3
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- - Pytorch 2.2.2+cu121
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  - Datasets 2.18.0
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  - Tokenizers 0.15.2
 
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  This model is a fine-tuned version of [NLP-LTU/bertweet-large-sexism-detector](https://huggingface.co/NLP-LTU/bertweet-large-sexism-detector) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.9648
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+ - Icm: 0.2479
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+ - Icmnorm: 0.6258
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+ - Fmeasure: 0.7526
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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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  - 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: 10
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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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+ | 0.8774 | 1.0 | 771 | 1.1253 | -0.1346 | 0.4317 | 0.5634 |
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+ | 0.9551 | 2.0 | 1542 | 0.8275 | 0.1264 | 0.5641 | 0.7110 |
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+ | 0.9559 | 3.0 | 2313 | 0.9648 | 0.2479 | 0.6258 | 0.7526 |
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+ | 0.6926 | 4.0 | 3084 | 1.5632 | 0.1570 | 0.5797 | 0.7172 |
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+ | 0.4547 | 5.0 | 3855 | 1.8028 | 0.1284 | 0.5652 | 0.7098 |
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+ | 0.2611 | 6.0 | 4626 | 1.9528 | 0.2025 | 0.6027 | 0.7359 |
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+ | 0.1528 | 7.0 | 5397 | 2.1400 | 0.1119 | 0.5568 | 0.7073 |
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+ | 0.1173 | 8.0 | 6168 | 2.1909 | 0.1524 | 0.5773 | 0.7195 |
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+ | 0.1096 | 9.0 | 6939 | 2.4630 | 0.1166 | 0.5591 | 0.7073 |
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+ | 0.0535 | 10.0 | 7710 | 2.4917 | 0.1809 | 0.5918 | 0.7276 |
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  ### Framework versions
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+ - Transformers 4.38.2
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+ - Pytorch 2.3.0+cu121
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  - Datasets 2.18.0
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  - Tokenizers 0.15.2
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