| | --- |
| | license: mit |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: roberta-scarcasm-discriminator |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # roberta-scarcasm-discriminator |
| |
|
| | roberta-base |
| |
|
| | label0: unsarcasitic |
| |
|
| | label1: sarcastic |
| | The fine tune method in my github https://github.com/yangyangxusheng/Fine-tune-use-transformers |
| |
|
| | This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.1844 |
| | - Accuracy: 0.9698 |
| |
|
| | ## Model description |
| |
|
| | More information needed |
| |
|
| | ## Intended uses & limitations |
| |
|
| | More information needed |
| |
|
| | ## Training and evaluation data |
| |
|
| | More information needed |
| |
|
| | ## Training procedure |
| |
|
| | ### Training hyperparameters |
| |
|
| | The following hyperparameters were used during training: |
| | - learning_rate: 5e-05 |
| | - train_batch_size: 16 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - lr_scheduler_warmup_steps: 500 |
| | - num_epochs: 4 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 0.144 | 1.0 | 2179 | 0.2522 | 0.9215 | |
| | | 0.116 | 2.0 | 4358 | 0.2105 | 0.9530 | |
| | | 0.0689 | 3.0 | 6537 | 0.2015 | 0.9610 | |
| | | 0.028 | 4.0 | 8716 | 0.1844 | 0.9698 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.12.3 |
| | - Pytorch 1.9.0+cu111 |
| | - Datasets 1.15.1 |
| | - Tokenizers 0.10.3 |
| | |
