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--- |
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base_model: UBC-NLP/MARBERTv2 |
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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: Arsarcasm |
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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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# Arsarcasm |
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This model is a fine-tuned version of [UBC-NLP/MARBERTv2](https://huggingface.co/UBC-NLP/MARBERTv2) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3985 |
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- Accuracy: 0.8757 |
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- F1 Weighted: 0.8778 |
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- Roc Auc: 0.7900 |
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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: 8 |
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- eval_batch_size: 8 |
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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 | F1 Weighted | Roc Auc | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:-------:| |
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| 0.3098 | 1.0 | 1050 | 0.3747 | 0.8634 | 0.8383 | 0.6305 | |
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| 0.2456 | 2.0 | 2100 | 0.3985 | 0.8757 | 0.8778 | 0.7900 | |
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| 0.1446 | 3.0 | 3150 | 0.5968 | 0.8786 | 0.8711 | 0.7262 | |
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| 0.0932 | 4.0 | 4200 | 0.6484 | 0.8738 | 0.8737 | 0.7678 | |
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| 0.0556 | 5.0 | 5250 | 0.7629 | 0.8767 | 0.8745 | 0.7578 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.1.0 |
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- Tokenizers 0.15.2 |
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