hBERTv1_new_pretrain_48_stsb
This model is a fine-tuned version of gokuls/bert_12_layer_model_v1_complete_training_new_48 on the GLUE STSB dataset. It achieves the following results on the evaluation set:
- Loss: 1.5726
- Pearson: 0.5712
- Spearmanr: 0.5660
- Combined Score: 0.5686
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 | Pearson | Spearmanr | Combined Score |
---|---|---|---|---|---|---|
2.4091 | 1.0 | 45 | 2.3547 | 0.1191 | 0.1028 | 0.1109 |
2.0478 | 2.0 | 90 | 2.4073 | 0.1413 | 0.1417 | 0.1415 |
1.8232 | 3.0 | 135 | 2.2454 | 0.2345 | 0.2627 | 0.2486 |
1.3631 | 4.0 | 180 | 1.9067 | 0.4891 | 0.4765 | 0.4828 |
1.2243 | 5.0 | 225 | 2.2429 | 0.4693 | 0.4507 | 0.4600 |
0.9081 | 6.0 | 270 | 1.7410 | 0.5250 | 0.5197 | 0.5224 |
0.7373 | 7.0 | 315 | 1.5726 | 0.5712 | 0.5660 | 0.5686 |
0.5958 | 8.0 | 360 | 1.8736 | 0.5183 | 0.5104 | 0.5143 |
0.5189 | 9.0 | 405 | 2.2244 | 0.5154 | 0.5137 | 0.5146 |
0.4191 | 10.0 | 450 | 1.8942 | 0.5165 | 0.5105 | 0.5135 |
0.3765 | 11.0 | 495 | 1.7040 | 0.5749 | 0.5652 | 0.5700 |
0.3326 | 12.0 | 540 | 1.7679 | 0.5656 | 0.5625 | 0.5641 |
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/hBERTv1_new_pretrain_48_stsb
Evaluation results
- Spearmanr on GLUE STSBvalidation set self-reported0.566