add_BERT_24_qnli
This model is a fine-tuned version of gokuls/add_bert_12_layer_model_complete_training_new on the GLUE QNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.6883
- Accuracy: 0.5416
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 | Accuracy |
---|---|---|---|---|
0.6964 | 1.0 | 819 | 0.6927 | 0.5171 |
0.6946 | 2.0 | 1638 | 0.6927 | 0.4946 |
0.6936 | 3.0 | 2457 | 0.6915 | 0.5200 |
0.6998 | 4.0 | 3276 | 0.6902 | 0.4946 |
0.6925 | 5.0 | 4095 | 0.6933 | 0.5257 |
0.6917 | 6.0 | 4914 | 0.6893 | 0.5274 |
0.6914 | 7.0 | 5733 | 0.6894 | 0.5294 |
0.6916 | 8.0 | 6552 | 0.6888 | 0.5382 |
0.6913 | 9.0 | 7371 | 0.6883 | 0.5416 |
0.6909 | 10.0 | 8190 | 0.6892 | 0.5356 |
0.6914 | 11.0 | 9009 | 0.6892 | 0.5411 |
0.6918 | 12.0 | 9828 | 0.6907 | 0.5257 |
0.6911 | 13.0 | 10647 | 0.6905 | 0.5286 |
0.6909 | 14.0 | 11466 | 0.6896 | 0.5319 |
Framework versions
- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.0
- Tokenizers 0.13.3
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Dataset used to train gokuls/add_BERT_24_qnli
Evaluation results
- Accuracy on GLUE QNLIvalidation set self-reported0.542