metadata
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: microsoft/deberta-v3-large
model-index:
- name: deberta-v3-large__sst2__train-32-0
results: []
deberta-v3-large__sst2__train-32-0
This model is a fine-tuned version of microsoft/deberta-v3-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4849
- Accuracy: 0.7716
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: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7059 | 1.0 | 13 | 0.6840 | 0.5385 |
| 0.6595 | 2.0 | 26 | 0.6214 | 0.6923 |
| 0.4153 | 3.0 | 39 | 0.1981 | 0.9231 |
| 0.0733 | 4.0 | 52 | 0.5068 | 0.9231 |
| 0.2092 | 5.0 | 65 | 1.3114 | 0.6923 |
| 0.003 | 6.0 | 78 | 1.1062 | 0.8462 |
| 0.0012 | 7.0 | 91 | 1.5948 | 0.7692 |
| 0.0008 | 8.0 | 104 | 1.6913 | 0.7692 |
| 0.0006 | 9.0 | 117 | 1.7191 | 0.7692 |
| 0.0005 | 10.0 | 130 | 1.6527 | 0.7692 |
| 0.0003 | 11.0 | 143 | 1.4840 | 0.7692 |
| 0.0002 | 12.0 | 156 | 1.3076 | 0.8462 |
| 0.0002 | 13.0 | 169 | 1.3130 | 0.8462 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3