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FNetHateSpeechClassification

Text Classification
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big_bird
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  1. README.md +15 -11
  2. model.safetensors +1 -1
README.md CHANGED
@@ -7,19 +7,19 @@ tags:
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  metrics:
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  - accuracy
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  model-index:
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- - name: BigBirdHateSpeechClassification
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  results: []
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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- # BigBirdHateSpeechClassification
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  This model is a fine-tuned version of [google/bigbird-roberta-base](https://huggingface.co/google/bigbird-roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7086
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- - Accuracy: 0.8055
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  ## Model description
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@@ -48,13 +48,17 @@ The following hyperparameters were used during training:
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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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- | 0.5447 | 1.0 | 1137 | 0.5022 | 0.7879 |
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- | 0.4304 | 2.0 | 2274 | 0.4451 | 0.7934 |
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- | 0.3615 | 3.0 | 3411 | 0.5008 | 0.8143 |
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- | 0.3192 | 4.0 | 4548 | 0.6437 | 0.8077 |
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- | 0.2483 | 5.0 | 5685 | 0.7086 | 0.8055 |
 
 
 
 
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  ### Framework versions
 
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  metrics:
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  - accuracy
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  model-index:
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+ - name: FNetHateSpeechClassification
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  results: []
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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+ # FNetHateSpeechClassification
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  This model is a fine-tuned version of [google/bigbird-roberta-base](https://huggingface.co/google/bigbird-roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6932
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+ - Accuracy: 0.4802
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  ## Model description
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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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+ | 0.6965 | 1.0 | 1137 | 0.6932 | 0.4802 |
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+ | 0.6943 | 2.0 | 2274 | 0.6927 | 0.5198 |
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+ | 0.6949 | 3.0 | 3411 | 0.6949 | 0.4802 |
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+ | 0.6941 | 4.0 | 4548 | 0.6936 | 0.4802 |
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+ | 0.6939 | 5.0 | 5685 | 0.6926 | 0.5198 |
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+ | 0.6937 | 6.0 | 6822 | 0.6926 | 0.5198 |
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+ | 0.6937 | 7.0 | 7959 | 0.6935 | 0.4802 |
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+ | 0.694 | 8.0 | 9096 | 0.6936 | 0.4802 |
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+ | 0.6934 | 9.0 | 10233 | 0.6932 | 0.4802 |
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  ### Framework versions
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