sa_BERT_no_pretrain_cola
This model is a fine-tuned version of on the GLUE COLA dataset. It achieves the following results on the evaluation set:
- Loss: 0.6180
- Matthews Correlation: 0.0
- Accuracy: 0.6913
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: 0.0005
- 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation | Accuracy |
|---|---|---|---|---|---|
| 0.8826 | 1.0 | 67 | 0.6624 | 0.0 | 0.6913 |
| 0.616 | 2.0 | 134 | 0.6358 | 0.0 | 0.6913 |
| 0.6134 | 3.0 | 201 | 0.6195 | 0.0 | 0.6913 |
| 0.6139 | 4.0 | 268 | 0.6285 | 0.0 | 0.6913 |
| 0.6117 | 5.0 | 335 | 0.6180 | 0.0 | 0.6913 |
| 0.6099 | 6.0 | 402 | 0.6183 | 0.0 | 0.6913 |
| 0.6113 | 7.0 | 469 | 0.6232 | 0.0 | 0.6913 |
| 0.6135 | 8.0 | 536 | 0.6182 | 0.0 | 0.6913 |
| 0.6094 | 9.0 | 603 | 0.6221 | 0.0 | 0.6913 |
| 0.6096 | 10.0 | 670 | 0.6310 | 0.0 | 0.6913 |
Framework versions
- Transformers 4.29.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3
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Dataset used to train gokuls/sa_BERT_no_pretrain_cola
Evaluation results
- Matthews Correlation on GLUE COLAvalidation set self-reported0.000
- Accuracy on GLUE COLAvalidation set self-reported0.691