deberta-v3-large-finetuned-sst2
This model is a fine-tuned version of microsoft/deberta-v3-large on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.1258
- Accuracy: 0.9622
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: 0.0005
- train_batch_size: 16
- eval_batch_size: 16
- seed: 0
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.1173 | 1.0 | 4210 | 0.1258 | 0.9622 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
Model tree for kibru/deberta-v3-large-finetuned-sst2
Base model
microsoft/deberta-v3-large