hBERTv2_new_pretrain_48_KD_cola
This model is a fine-tuned version of gokuls/bert_12_layer_model_v2_complete_training_new_48_KD on the GLUE COLA dataset. It achieves the following results on the evaluation set:
- Loss: 0.6132
- Matthews Correlation: 0.0647
- Accuracy: 0.6779
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: 4e-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 | Matthews Correlation | Accuracy |
---|---|---|---|---|---|
0.6252 | 1.0 | 67 | 0.6183 | 0.0 | 0.6913 |
0.6155 | 2.0 | 134 | 0.6184 | 0.0 | 0.6913 |
0.6098 | 3.0 | 201 | 0.6132 | 0.0647 | 0.6779 |
0.6009 | 4.0 | 268 | 0.6308 | 0.0985 | 0.6779 |
0.5755 | 5.0 | 335 | 0.6287 | 0.0766 | 0.6894 |
0.5478 | 6.0 | 402 | 0.6476 | 0.0967 | 0.6625 |
0.5158 | 7.0 | 469 | 0.7149 | 0.0667 | 0.6539 |
0.4864 | 8.0 | 536 | 0.6457 | 0.0789 | 0.6500 |
Framework versions
- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3
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Dataset used to train gokuls/hBERTv2_new_pretrain_48_KD_cola
Evaluation results
- Matthews Correlation on GLUE COLAvalidation set self-reported0.065
- Accuracy on GLUE COLAvalidation set self-reported0.678