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XLMHateSpeechClassification

Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Model card Files
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  1. README.md +13 -13
  2. model.safetensors +1 -1
README.md CHANGED
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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/muril-base-cased
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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: MuRILHateSpeechClassification
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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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- # MuRILHateSpeechClassification
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- This model is a fine-tuned version of [google/muril-base-cased](https://huggingface.co/google/muril-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7371
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- - Accuracy: 0.8407
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  ## Model description
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@@ -50,12 +50,12 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.5519 | 1.0 | 1137 | 0.4704 | 0.8110 |
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- | 0.4345 | 2.0 | 2274 | 0.4862 | 0.8198 |
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- | 0.3547 | 3.0 | 3411 | 0.4660 | 0.8473 |
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- | 0.2919 | 4.0 | 4548 | 0.6066 | 0.8440 |
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- | 0.2205 | 5.0 | 5685 | 0.6805 | 0.8429 |
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- | 0.1759 | 6.0 | 6822 | 0.7371 | 0.8407 |
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  ### Framework versions
 
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  ---
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  library_name: transformers
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+ license: mit
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+ base_model: FacebookAI/xlm-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: XLMHateSpeechClassification
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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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+ # XLMHateSpeechClassification
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+ This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.7826
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+ - Accuracy: 0.8319
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.5749 | 1.0 | 1137 | 0.5185 | 0.7780 |
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+ | 0.4785 | 2.0 | 2274 | 0.5458 | 0.7681 |
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+ | 0.4545 | 3.0 | 3411 | 0.4246 | 0.8154 |
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+ | 0.3938 | 4.0 | 4548 | 0.5763 | 0.8176 |
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+ | 0.3554 | 5.0 | 5685 | 0.6506 | 0.8154 |
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+ | 0.3368 | 6.0 | 6822 | 0.7826 | 0.8319 |
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  ### Framework versions
model.safetensors CHANGED
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