metadata
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: microsoft/deberta-v3-large
model-index:
- name: deberta-v3-large__sst2__train-16-5
results: []
deberta-v3-large__sst2__train-16-5
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: 0.5433
- Accuracy: 0.7924
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 |
|---|---|---|---|---|
| 0.6774 | 1.0 | 7 | 0.7450 | 0.2857 |
| 0.7017 | 2.0 | 14 | 0.7552 | 0.2857 |
| 0.6438 | 3.0 | 21 | 0.7140 | 0.4286 |
| 0.3525 | 4.0 | 28 | 0.5570 | 0.7143 |
| 0.2061 | 5.0 | 35 | 0.5303 | 0.8571 |
| 0.0205 | 6.0 | 42 | 0.6706 | 0.8571 |
| 0.0068 | 7.0 | 49 | 0.8284 | 0.8571 |
| 0.0029 | 8.0 | 56 | 0.9281 | 0.8571 |
| 0.0015 | 9.0 | 63 | 0.9871 | 0.8571 |
| 0.0013 | 10.0 | 70 | 1.0208 | 0.8571 |
| 0.0008 | 11.0 | 77 | 1.0329 | 0.8571 |
| 0.0005 | 12.0 | 84 | 1.0348 | 0.8571 |
| 0.0004 | 13.0 | 91 | 1.0437 | 0.8571 |
| 0.0005 | 14.0 | 98 | 1.0512 | 0.8571 |
| 0.0004 | 15.0 | 105 | 1.0639 | 0.8571 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3