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--- |
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license: mit |
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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: roberta-scarcasm-discriminator |
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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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# roberta-scarcasm-discriminator |
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roberta-base |
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label0: unsarcasitic |
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label1: sarcastic |
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The fine tune method in my github https://github.com/yangyangxusheng/Fine-tune-use-transformers |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1844 |
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- Accuracy: 0.9698 |
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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-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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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 4 |
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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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| 0.144 | 1.0 | 2179 | 0.2522 | 0.9215 | |
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| 0.116 | 2.0 | 4358 | 0.2105 | 0.9530 | |
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| 0.0689 | 3.0 | 6537 | 0.2015 | 0.9610 | |
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| 0.028 | 4.0 | 8716 | 0.1844 | 0.9698 | |
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### Framework versions |
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- Transformers 4.12.3 |
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- Pytorch 1.9.0+cu111 |
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- Datasets 1.15.1 |
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- Tokenizers 0.10.3 |
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