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--- |
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license: apache-2.0 |
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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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base_model: distilbert-base-uncased |
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model-index: |
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- name: distilbert-base-uncased__hate_speech_offensive__train-32-5 |
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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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# distilbert-base-uncased__hate_speech_offensive__train-32-5 |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1327 |
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- Accuracy: 0.57 |
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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: 4 |
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- eval_batch_size: 4 |
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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: 50 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 1.0972 | 1.0 | 19 | 1.0470 | 0.45 | |
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| 0.9738 | 2.0 | 38 | 0.9244 | 0.65 | |
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| 0.7722 | 3.0 | 57 | 0.8612 | 0.65 | |
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| 0.4929 | 4.0 | 76 | 0.6759 | 0.75 | |
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| 0.2435 | 5.0 | 95 | 0.7273 | 0.7 | |
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| 0.0929 | 6.0 | 114 | 0.6444 | 0.85 | |
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| 0.0357 | 7.0 | 133 | 0.7671 | 0.8 | |
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| 0.0173 | 8.0 | 152 | 0.7599 | 0.75 | |
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| 0.0121 | 9.0 | 171 | 0.8140 | 0.8 | |
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| 0.0081 | 10.0 | 190 | 0.7861 | 0.8 | |
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| 0.0066 | 11.0 | 209 | 0.8318 | 0.8 | |
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| 0.0057 | 12.0 | 228 | 0.8777 | 0.8 | |
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| 0.0053 | 13.0 | 247 | 0.8501 | 0.8 | |
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| 0.004 | 14.0 | 266 | 0.8603 | 0.8 | |
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| 0.004 | 15.0 | 285 | 0.8787 | 0.8 | |
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| 0.0034 | 16.0 | 304 | 0.8969 | 0.8 | |
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### Framework versions |
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- Transformers 4.15.0 |
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- Pytorch 1.10.2+cu102 |
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- Datasets 1.18.2 |
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- Tokenizers 0.10.3 |
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