hBERTv1_data_aug_mrpc
This model is a fine-tuned version of gokuls/bert_12_layer_model_v1 on the GLUE MRPC dataset. It achieves the following results on the evaluation set:
- Loss: 0.0001
- 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: 256
- eval_batch_size: 256
- 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score |
|---|---|---|---|---|---|---|
| 0.1151 | 1.0 | 980 | 0.0045 | 0.9975 | 0.9982 | 0.9979 |
| 0.0108 | 2.0 | 1960 | 0.0001 | 1.0 | 1.0 | 1.0 |
| 0.0063 | 3.0 | 2940 | 0.0001 | 1.0 | 1.0 | 1.0 |
| 0.0054 | 4.0 | 3920 | 0.0001 | 1.0 | 1.0 | 1.0 |
| 0.004 | 5.0 | 4900 | 0.0001 | 1.0 | 1.0 | 1.0 |
| 0.0053 | 6.0 | 5880 | 0.0002 | 1.0 | 1.0 | 1.0 |
| 0.0046 | 7.0 | 6860 | 0.0003 | 1.0 | 1.0 | 1.0 |
| 0.0116 | 8.0 | 7840 | 0.0150 | 0.9975 | 0.9982 | 0.9979 |
| 0.0093 | 9.0 | 8820 | 0.0015 | 1.0 | 1.0 | 1.0 |
| 0.0123 | 10.0 | 9800 | 0.0164 | 0.9975 | 0.9982 | 0.9979 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.14.0a0+410ce96
- Datasets 2.10.1
- Tokenizers 0.13.2
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Dataset used to train gokuls/hBERTv1_data_aug_mrpc
Evaluation results
- Accuracy on GLUE MRPCself-reported1.000
- F1 on GLUE MRPCself-reported1.000