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tiny-bert-sst2-1_mobilebert_2_bert_3_gold_labels-distillation
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: 0.9350
- Accuracy: 0.8188
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 33
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1041 | 1.0 | 4210 | 0.9350 | 0.8188 |
| 0.1166 | 2.0 | 8420 | 0.9179 | 0.8188 |
| 0.1127 | 3.0 | 12630 | 0.9083 | 0.8142 |
| 0.1163 | 4.0 | 16840 | 0.9087 | 0.8165 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
