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Fine-tuned on hate speech dataset

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  2. model.safetensors +1 -1
README.md ADDED
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+ ---
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+ base_model: facebook/roberta-hate-speech-dynabench-r4-target
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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: facebook-hate-speech-fine-tuned
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+ results: []
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+ ---
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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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+
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+ # facebook-hate-speech-fine-tuned
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+
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+ This model is a fine-tuned version of [facebook/roberta-hate-speech-dynabench-r4-target](https://huggingface.co/facebook/roberta-hate-speech-dynabench-r4-target) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1943
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+ - Accuracy: 0.9636
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+ - Precision Macro: 0.8675
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+ - Recall Macro: 0.8731
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+ - F1 Macro: 0.8703
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+ - Precision Micro: 0.9636
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+ - Recall Micro: 0.9636
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+ - F1 Micro: 0.9636
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Macro | Recall Macro | F1 Macro | Precision Micro | Recall Micro | F1 Micro |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|:--------:|
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+ | 0.2628 | 1.0 | 199 | 0.1203 | 0.9585 | 0.8840 | 0.7939 | 0.8318 | 0.9585 | 0.9585 | 0.9585 |
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+ | 0.071 | 2.0 | 398 | 0.1640 | 0.9673 | 0.9144 | 0.8369 | 0.8709 | 0.9673 | 0.9673 | 0.9673 |
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+ | 0.1483 | 3.0 | 597 | 0.1943 | 0.9636 | 0.8675 | 0.8731 | 0.8703 | 0.9636 | 0.9636 | 0.9636 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.42.4
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+ - Pytorch 2.4.0+cu121
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+ - Datasets 2.21.0
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+ - Tokenizers 0.19.1
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