bert_distillation_0
This model is a fine-tuned version of google/bert_uncased_L-2_H-128_A-2 on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 1.1784
- Accuracy: 0.8303
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: 0.0001
- train_batch_size: 128
- eval_batch_size: 128
- seed: 2023
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.2697 | 1.0 | 527 | 1.0445 | 0.8200 |
| 0.6784 | 2.0 | 1054 | 1.0168 | 0.8177 |
| 0.5206 | 3.0 | 1581 | 1.1356 | 0.8108 |
| 0.4383 | 4.0 | 2108 | 1.1437 | 0.8280 |
| 0.3844 | 5.0 | 2635 | 1.1687 | 0.8268 |
| 0.3547 | 6.0 | 3162 | 1.1784 | 0.8303 |
| 0.3373 | 7.0 | 3689 | 1.2045 | 0.8280 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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Base model
google/bert_uncased_L-2_H-128_A-2