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roberta-base-finetuned-sst2
This model is a fine-tuned version of roberta-base on the scim dataset. It achieves the following results on the evaluation set:
- Loss: 0.4632
- Accuracy: 0.9111
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 90 | 2.0273 | 0.6667 |
| No log | 2.0 | 180 | 0.8802 | 0.8556 |
| No log | 3.0 | 270 | 0.5908 | 0.8889 |
| No log | 4.0 | 360 | 0.4632 | 0.9111 |
| No log | 5.0 | 450 | 0.4294 | 0.9111 |
Framework versions
- Transformers 4.9.1
- Pytorch 1.9.0+cu102
- Datasets 1.11.0
- Tokenizers 0.10.3
