hBERTv1_data_aug_rte
This model is a fine-tuned version of gokuls/bert_12_layer_model_v1 on the GLUE RTE dataset. It achieves the following results on the evaluation set:
- Loss: 2.3280
- Accuracy: 0.5199
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 |
|---|---|---|---|---|
| 0.2316 | 1.0 | 568 | 2.3280 | 0.5199 |
| 0.0234 | 2.0 | 1136 | 3.0592 | 0.5271 |
| 0.0106 | 3.0 | 1704 | 3.6972 | 0.5054 |
| 0.0067 | 4.0 | 2272 | 3.2471 | 0.4765 |
| 0.0051 | 5.0 | 2840 | 3.3428 | 0.5090 |
| 0.0037 | 6.0 | 3408 | 3.9613 | 0.5054 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.14.0a0+410ce96
- Datasets 2.10.1
- Tokenizers 0.13.2