hBERTv2_rte
This model is a fine-tuned version of gokuls/bert_12_layer_model_v2 on the GLUE RTE dataset. It achieves the following results on the evaluation set:
- Loss: 0.6896
- Accuracy: 0.5487
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 |
|---|---|---|---|---|
| 0.7231 | 1.0 | 10 | 0.7175 | 0.4549 |
| 0.702 | 2.0 | 20 | 0.7053 | 0.4729 |
| 0.6982 | 3.0 | 30 | 0.6976 | 0.4585 |
| 0.7008 | 4.0 | 40 | 0.7261 | 0.4657 |
| 0.7022 | 5.0 | 50 | 0.7142 | 0.4946 |
| 0.6867 | 6.0 | 60 | 0.6943 | 0.4801 |
| 0.6796 | 7.0 | 70 | 0.6896 | 0.5487 |
| 0.6614 | 8.0 | 80 | 0.7151 | 0.5162 |
| 0.6303 | 9.0 | 90 | 0.7244 | 0.5271 |
| 0.602 | 10.0 | 100 | 0.7570 | 0.4729 |
| 0.5761 | 11.0 | 110 | 0.7605 | 0.5379 |
| 0.5664 | 12.0 | 120 | 0.8160 | 0.5235 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.14.0a0+410ce96
- Datasets 2.10.1
- Tokenizers 0.13.2
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