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mobilebert_add_GLUE_Experiment_logit_kd_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: 0.8027
- Accuracy: 0.7596
- F1: 0.6364
- Combined Score: 0.6980
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 |
|---|---|---|---|---|---|---|
| 1.2838 | 1.0 | 2843 | 1.2200 | 0.6318 | 0.0 | 0.3159 |
| 1.0184 | 2.0 | 5686 | 0.8422 | 0.7473 | 0.5924 | 0.6698 |
| 0.8633 | 3.0 | 8529 | 0.8232 | 0.7520 | 0.5963 | 0.6742 |
| 0.834 | 4.0 | 11372 | 0.8193 | 0.7563 | 0.6271 | 0.6917 |
| 0.812 | 5.0 | 14215 | 0.8027 | 0.7596 | 0.6364 | 0.6980 |
| 0.7871 | 6.0 | 17058 | nan | 0.6318 | 0.0 | 0.3159 |
| 0.0 | 7.0 | 19901 | nan | 0.6318 | 0.0 | 0.3159 |
| 0.0 | 8.0 | 22744 | nan | 0.6318 | 0.0 | 0.3159 |
| 0.0 | 9.0 | 25587 | nan | 0.6318 | 0.0 | 0.3159 |
| 0.0 | 10.0 | 28430 | nan | 0.6318 | 0.0 | 0.3159 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.9.0
- Tokenizers 0.13.2
