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End of training

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  1. README.md +12 -17
  2. model.safetensors +1 -1
README.md CHANGED
@@ -1,25 +1,25 @@
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  ---
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  library_name: transformers
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  license: apache-2.0
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- base_model: google/bigbird-roberta-base
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  tags:
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  - generated_from_trainer
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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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@@ -48,17 +48,12 @@ 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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- | 0.6965 | 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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  ---
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  library_name: transformers
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  license: apache-2.0
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+ base_model: sentence-transformers/all-mpnet-base-v2
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  tags:
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  - generated_from_trainer
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  metrics:
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  - accuracy
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  model-index:
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+ - name: MPNetHateSpeechClassification
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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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+ # MPNetHateSpeechClassification
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+ This model is a fine-tuned version of [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5997
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+ - Accuracy: 0.8209
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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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+ | 0.4898 | 1.0 | 1137 | 0.4641 | 0.7901 |
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+ | 0.3714 | 2.0 | 2274 | 0.4775 | 0.8220 |
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+ | 0.3115 | 3.0 | 3411 | 0.5572 | 0.8308 |
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+ | 0.2401 | 4.0 | 4548 | 0.5997 | 0.8209 |
 
 
 
 
 
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  ### Framework versions
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@@ -1,3 +1,3 @@
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