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hBERTv1_new_pretrain_w_init_48_ver2_cola
This model is a fine-tuned version of gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48 on the GLUE COLA dataset. It achieves the following results on the evaluation set:
- Loss: 0.6179
- 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: 4e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
Training Loss | Epoch | Step | Validation Loss | Matthews Correlation | Accuracy |
---|---|---|---|---|---|
0.6277 | 1.0 | 134 | 0.6457 | 0.0 | 0.6913 |
0.6178 | 2.0 | 268 | 0.6240 | 0.0 | 0.6913 |
0.6152 | 3.0 | 402 | 0.6201 | 0.0 | 0.6913 |
0.6138 | 4.0 | 536 | 0.6181 | 0.0 | 0.6913 |
0.6111 | 5.0 | 670 | 0.6181 | 0.0 | 0.6913 |
0.6122 | 6.0 | 804 | 0.6232 | 0.0 | 0.6913 |
0.611 | 7.0 | 938 | 0.6179 | 0.0 | 0.6913 |
0.6087 | 8.0 | 1072 | 0.6182 | 0.0 | 0.6913 |
0.6112 | 9.0 | 1206 | 0.6226 | 0.0 | 0.6913 |
0.6116 | 10.0 | 1340 | 0.6210 | 0.0 | 0.6913 |
0.6091 | 11.0 | 1474 | 0.6194 | 0.0 | 0.6913 |
0.6087 | 12.0 | 1608 | 0.6184 | 0.0 | 0.6913 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.1