Fine-tuned on hate speech dataset
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README.md
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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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<!-- 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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# facebook-hate-speech-fine-tuned
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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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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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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: 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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### Training results
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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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### Framework versions
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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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model.safetensors
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