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mobilebert_sa_GLUE_Experiment_qqp_256
This model is a fine-tuned version of google/mobilebert-uncased on the GLUE QQP dataset. It achieves the following results on the evaluation set:
- Loss: 0.4349
- Accuracy: 0.7976
- F1: 0.7297
- Combined Score: 0.7637
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: 128
- eval_batch_size: 128
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score |
|---|---|---|---|---|---|---|
| 0.526 | 1.0 | 2843 | 0.5088 | 0.7492 | 0.6674 | 0.7083 |
| 0.4762 | 2.0 | 5686 | 0.4782 | 0.7695 | 0.6583 | 0.7139 |
| 0.4438 | 3.0 | 8529 | 0.4532 | 0.7847 | 0.6829 | 0.7338 |
| 0.4161 | 4.0 | 11372 | 0.4602 | 0.7869 | 0.7135 | 0.7502 |
| 0.3968 | 5.0 | 14215 | 0.4395 | 0.7955 | 0.7212 | 0.7583 |
| 0.3815 | 6.0 | 17058 | 0.4392 | 0.7985 | 0.7190 | 0.7587 |
| 0.3659 | 7.0 | 19901 | 0.4349 | 0.7976 | 0.7297 | 0.7637 |
| 0.352 | 8.0 | 22744 | 0.4419 | 0.8005 | 0.7300 | 0.7652 |
| 0.3399 | 9.0 | 25587 | 0.4454 | 0.7998 | 0.7317 | 0.7658 |
| 0.327 | 10.0 | 28430 | 0.4614 | 0.7995 | 0.7359 | 0.7677 |
| 0.3157 | 11.0 | 31273 | 0.4733 | 0.8000 | 0.7246 | 0.7623 |
| 0.3041 | 12.0 | 34116 | 0.4738 | 0.8041 | 0.7283 | 0.7662 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.8.0
- Tokenizers 0.13.2
