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--- |
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license: apache-2.0 |
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base_model: bert-large-uncased |
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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: bert-large-uncased-Hate_Offensive_or_Normal_Speech |
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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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# bert-large-uncased-Hate_Offensive_or_Normal_Speech |
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This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0610 |
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- Accuracy: 0.9853 |
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- Weighted f1: 0.9853 |
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- Weighted recall: 0.9853 |
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- Weighted precision: 0.9854 |
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- Micro f1: 0.9853 |
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- Micro recall: 0.9853 |
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- Micro precision: 0.9853 |
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- Macro f1: 0.9851 |
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- Macro recall: 0.9850 |
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- Macro precision: 0.9853 |
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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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 | Weighted recall | Weighted precision | Micro f1 | Micro recall | Micro precision | Macro f1 | Macro recall | Macro precision | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:---------------:|:------------------:|:--------:|:------------:|:---------------:|:--------:|:------------:|:---------------:| |
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| 0.2927 | 1.0 | 153 | 0.1163 | 0.9462 | 0.9469 | 0.9462 | 0.9512 | 0.9462 | 0.9462 | 0.9462 | 0.9429 | 0.9472 | 0.9427 | |
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| 0.066 | 2.0 | 306 | 0.1119 | 0.9739 | 0.9739 | 0.9739 | 0.9741 | 0.9739 | 0.9739 | 0.9739 | 0.9729 | 0.9742 | 0.9718 | |
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| 0.0267 | 3.0 | 459 | 0.0805 | 0.9821 | 0.9821 | 0.9821 | 0.9825 | 0.9821 | 0.9821 | 0.9821 | 0.9804 | 0.9815 | 0.9796 | |
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| 0.0209 | 4.0 | 612 | 0.0610 | 0.9853 | 0.9853 | 0.9853 | 0.9854 | 0.9853 | 0.9853 | 0.9853 | 0.9851 | 0.9850 | 0.9853 | |
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| 0.0097 | 5.0 | 765 | 0.0673 | 0.9837 | 0.9836 | 0.9837 | 0.9838 | 0.9837 | 0.9837 | 0.9837 | 0.9832 | 0.9833 | 0.9833 | |
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### Framework versions |
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- Transformers 4.34.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.6.dev0 |
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- Tokenizers 0.13.3 |
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