mobilebert_sa_GLUE_Experiment_data_aug_mrpc
This model is a fine-tuned version of google/mobilebert-uncased on the GLUE MRPC dataset. It achieves the following results on the evaluation set:
- Loss: 0.0000
- Accuracy: 1.0
- F1: 1.0
- Combined Score: 1.0
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 |
---|---|---|---|---|---|---|
0.1838 | 1.0 | 1959 | 0.0138 | 0.9951 | 0.9964 | 0.9958 |
0.0406 | 2.0 | 3918 | 0.0055 | 1.0 | 1.0 | 1.0 |
0.0267 | 3.0 | 5877 | 0.0129 | 0.9975 | 0.9982 | 0.9979 |
0.0151 | 4.0 | 7836 | 0.0004 | 1.0 | 1.0 | 1.0 |
0.0108 | 5.0 | 9795 | 0.0104 | 0.9975 | 0.9982 | 0.9979 |
0.0075 | 6.0 | 11754 | 0.0000 | 1.0 | 1.0 | 1.0 |
0.0059 | 7.0 | 13713 | 0.0005 | 1.0 | 1.0 | 1.0 |
0.0047 | 8.0 | 15672 | 0.0000 | 1.0 | 1.0 | 1.0 |
0.0033 | 9.0 | 17631 | 0.0001 | 1.0 | 1.0 | 1.0 |
0.0031 | 10.0 | 19590 | 0.0000 | 1.0 | 1.0 | 1.0 |
0.0025 | 11.0 | 21549 | 0.0000 | 1.0 | 1.0 | 1.0 |
0.0019 | 12.0 | 23508 | 0.0000 | 1.0 | 1.0 | 1.0 |
0.0019 | 13.0 | 25467 | 0.0000 | 1.0 | 1.0 | 1.0 |
0.0014 | 14.0 | 27426 | 0.0000 | 1.0 | 1.0 | 1.0 |
0.001 | 15.0 | 29385 | 0.0000 | 1.0 | 1.0 | 1.0 |
0.001 | 16.0 | 31344 | 0.0000 | 1.0 | 1.0 | 1.0 |
0.0009 | 17.0 | 33303 | 0.0000 | 1.0 | 1.0 | 1.0 |
0.0009 | 18.0 | 35262 | 0.0000 | 1.0 | 1.0 | 1.0 |
0.0006 | 19.0 | 37221 | 0.0000 | 1.0 | 1.0 | 1.0 |
0.0006 | 20.0 | 39180 | 0.0000 | 1.0 | 1.0 | 1.0 |
0.0003 | 21.0 | 41139 | 0.0000 | 1.0 | 1.0 | 1.0 |
0.0003 | 22.0 | 43098 | 0.0000 | 1.0 | 1.0 | 1.0 |
0.0005 | 23.0 | 45057 | 0.0000 | 1.0 | 1.0 | 1.0 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.9.0
- Tokenizers 0.13.2
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Dataset used to train gokuls/mobilebert_sa_GLUE_Experiment_data_aug_mrpc
Evaluation results
- Accuracy on GLUE MRPCself-reported1.000
- F1 on GLUE MRPCself-reported1.000