marbert-finetuned-wanlp_sarcasm
This model is a fine-tuned version of UBC-NLP/MARBERT on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6362
- Accuracy: 0.9485
- Precision: 0.7758
- Recall: 0.7814
- F1: 0.7786
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.2904 | 1.0 | 226 | 0.4947 | 0.9402 | 0.8199 | 0.6201 | 0.7061 |
| 0.2199 | 2.0 | 452 | 0.4060 | 0.9406 | 0.7345 | 0.7634 | 0.7487 |
| 0.0545 | 3.0 | 678 | 0.6362 | 0.9485 | 0.7758 | 0.7814 | 0.7786 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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Base model
UBC-NLP/MARBERT