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--- |
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library_name: transformers |
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base_model: cardiffnlp/twitter-roberta-base-hate |
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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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- precision |
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- recall |
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model-index: |
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- name: twitter-roberta-base-hate_1337 |
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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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# twitter-roberta-base-hate_1337 |
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This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-hate](https://huggingface.co/cardiffnlp/twitter-roberta-base-hate) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3885 |
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- F1-score: 0.8487 |
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- Accuracy: 0.8497 |
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- Precision: 0.8478 |
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- Recall: 0.8521 |
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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: 5e-06 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 1337 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 6 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1-score | Accuracy | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:| |
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| No log | 1.0 | 180 | 0.3770 | 0.8354 | 0.8357 | 0.8388 | 0.8430 | |
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| No log | 2.0 | 360 | 0.3682 | 0.8334 | 0.8357 | 0.8332 | 0.8337 | |
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| 0.3667 | 3.0 | 540 | 0.3620 | 0.8521 | 0.8531 | 0.8511 | 0.8553 | |
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| 0.3667 | 4.0 | 720 | 0.3913 | 0.8334 | 0.8357 | 0.8332 | 0.8337 | |
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| 0.3667 | 5.0 | 900 | 0.3967 | 0.8303 | 0.8322 | 0.8295 | 0.8314 | |
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| 0.2409 | 6.0 | 1080 | 0.3885 | 0.8487 | 0.8497 | 0.8478 | 0.8521 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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