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mobilebert_sa_GLUE_Experiment_logit_kd_qqp
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: 0.6021
- Accuracy: 0.8081
- F1: 0.7357
- Combined Score: 0.7719
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 |
---|---|---|---|---|---|---|
0.9285 | 1.0 | 2843 | 0.8489 | 0.7517 | 0.6660 | 0.7089 |
0.7919 | 2.0 | 5686 | 0.7104 | 0.7735 | 0.6483 | 0.7109 |
0.6916 | 3.0 | 8529 | 0.6615 | 0.7900 | 0.6994 | 0.7447 |
0.6382 | 4.0 | 11372 | 0.6606 | 0.7899 | 0.6842 | 0.7370 |
0.6003 | 5.0 | 14215 | 0.6277 | 0.7988 | 0.7181 | 0.7585 |
0.5696 | 6.0 | 17058 | 0.6174 | 0.7980 | 0.7058 | 0.7519 |
0.5434 | 7.0 | 19901 | 0.6062 | 0.8036 | 0.7266 | 0.7651 |
0.5186 | 8.0 | 22744 | 0.6182 | 0.7995 | 0.7232 | 0.7614 |
0.4968 | 9.0 | 25587 | 0.6087 | 0.8052 | 0.7257 | 0.7654 |
0.4758 | 10.0 | 28430 | 0.6035 | 0.8073 | 0.7359 | 0.7716 |
0.456 | 11.0 | 31273 | 0.6021 | 0.8081 | 0.7357 | 0.7719 |
0.4361 | 12.0 | 34116 | 0.6137 | 0.8070 | 0.7366 | 0.7718 |
0.4186 | 13.0 | 36959 | 0.6282 | 0.8076 | 0.7416 | 0.7746 |
0.4009 | 14.0 | 39802 | 0.6183 | 0.8093 | 0.7445 | 0.7769 |
0.3846 | 15.0 | 42645 | 0.6196 | 0.8057 | 0.7483 | 0.7770 |
0.3699 | 16.0 | 45488 | 0.6381 | 0.8122 | 0.7426 | 0.7774 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.9.0
- Tokenizers 0.13.2