metadata
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: microsoft/deberta-v3-large
model-index:
- name: deberta-v3-large__sst2__train-16-4
results: []
deberta-v3-large__sst2__train-16-4
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: 0.6329
- Accuracy: 0.6392
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 |
---|---|---|---|---|
0.6945 | 1.0 | 7 | 0.7381 | 0.2857 |
0.7072 | 2.0 | 14 | 0.7465 | 0.2857 |
0.6548 | 3.0 | 21 | 0.7277 | 0.4286 |
0.5695 | 4.0 | 28 | 0.6738 | 0.5714 |
0.4615 | 5.0 | 35 | 0.8559 | 0.5714 |
0.0823 | 6.0 | 42 | 1.0983 | 0.5714 |
0.0274 | 7.0 | 49 | 1.9937 | 0.5714 |
0.0106 | 8.0 | 56 | 2.2209 | 0.5714 |
0.0039 | 9.0 | 63 | 2.2114 | 0.5714 |
0.0031 | 10.0 | 70 | 2.2808 | 0.5714 |
0.0013 | 11.0 | 77 | 2.3707 | 0.5714 |
0.0008 | 12.0 | 84 | 2.4902 | 0.5714 |
0.0005 | 13.0 | 91 | 2.5208 | 0.5714 |
0.0007 | 14.0 | 98 | 2.5683 | 0.5714 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3