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bert-distilled-model-flip_mind_epoch12_alpha0.8
This model is a fine-tuned version of ArafatBHossain/distill_bert_fine_tuned_mind on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.7953
- Accuracy: 0.914
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.8595 | 1.0 | 3054 | 1.8311 | 0.854 |
| 1.7769 | 2.0 | 6108 | 1.7204 | 0.847 |
| 1.7614 | 3.0 | 9162 | 1.7666 | 0.8666 |
| 1.7212 | 4.0 | 12216 | 1.8134 | 0.8716 |
| 1.7255 | 5.0 | 15270 | 1.7368 | 0.8812 |
| 1.6845 | 6.0 | 18324 | 1.7368 | 0.8898 |
| 1.7346 | 7.0 | 21378 | 1.6621 | 0.8936 |
| 1.7436 | 8.0 | 24432 | 1.7180 | 0.9008 |
| 1.7333 | 9.0 | 27486 | 1.7523 | 0.9048 |
| 1.7805 | 10.0 | 30540 | 1.7820 | 0.9078 |
| 1.792 | 11.0 | 33594 | 1.7329 | 0.9096 |
| 1.7463 | 12.0 | 36648 | 1.7953 | 0.914 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.11.0
- Datasets 2.6.1
- Tokenizers 0.12.1
