mobilebert_add_GLUE_Experiment_qqp_128
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: 0.5071
- Accuracy: 0.7568
- F1: 0.6361
- Combined Score: 0.6965
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 |
|---|---|---|---|---|---|---|
| 0.6507 | 1.0 | 2843 | 0.6497 | 0.6318 | 0.0 | 0.3159 |
| 0.6311 | 2.0 | 5686 | 0.5445 | 0.7259 | 0.5622 | 0.6441 |
| 0.5153 | 3.0 | 8529 | 0.5153 | 0.7493 | 0.5892 | 0.6693 |
| 0.4912 | 4.0 | 11372 | 0.5071 | 0.7568 | 0.6361 | 0.6965 |
| 0.4805 | 5.0 | 14215 | nan | 0.6318 | 0.0 | 0.3159 |
| 0.0 | 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 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.8.0
- Tokenizers 0.13.2
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Dataset used to train gokuls/mobilebert_add_GLUE_Experiment_qqp_128
Evaluation results
- Accuracy on GLUE QQPvalidation set self-reported0.757
- F1 on GLUE QQPvalidation set self-reported0.636