electra-distilled-sst
This model is a fine-tuned version of google/electra-small-discriminator on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3772
- Accuracy: 0.9174
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: 4.854751380955516e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 33
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 9
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3762 | 1.0 | 527 | 0.2865 | 0.9083 |
| 0.2105 | 2.0 | 1054 | 0.3472 | 0.9048 |
| 0.1566 | 3.0 | 1581 | 0.3098 | 0.9243 |
| 0.1221 | 4.0 | 2108 | 0.3681 | 0.9174 |
| 0.1029 | 5.0 | 2635 | 0.3772 | 0.9174 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.2.0
- Datasets 2.18.0
- Tokenizers 0.19.1