deberta-v3-large__sst2__train-8-7
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: 0.7037
- Accuracy: 0.5008
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 |
---|---|---|---|---|
0.6864 | 1.0 | 3 | 0.7800 | 0.25 |
0.6483 | 2.0 | 6 | 0.8067 | 0.25 |
0.6028 | 3.0 | 9 | 0.8500 | 0.25 |
0.4086 | 4.0 | 12 | 1.0661 | 0.25 |
0.2923 | 5.0 | 15 | 1.2302 | 0.25 |
0.2059 | 6.0 | 18 | 1.0312 | 0.5 |
0.1238 | 7.0 | 21 | 1.1271 | 0.5 |
0.0711 | 8.0 | 24 | 1.3100 | 0.5 |
0.0453 | 9.0 | 27 | 1.4208 | 0.5 |
0.0198 | 10.0 | 30 | 1.5988 | 0.5 |
0.0135 | 11.0 | 33 | 1.9174 | 0.5 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3
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