--- language: - en base_model: gokuls/bert_12_layer_model_v2_complete_training_new_48 tags: - generated_from_trainer datasets: - glue metrics: - spearmanr model-index: - name: hBERTv2_new_pretrain_48_ver2_stsb results: - task: name: Text Classification type: text-classification dataset: name: GLUE STSB type: glue config: stsb split: validation args: stsb metrics: - name: Spearmanr type: spearmanr value: 0.38294286179733106 --- # hBERTv2_new_pretrain_48_ver2_stsb This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2_complete_training_new_48](https://huggingface.co/gokuls/bert_12_layer_model_v2_complete_training_new_48) on the GLUE STSB dataset. It achieves the following results on the evaluation set: - Loss: 2.0659 - Pearson: 0.3927 - Spearmanr: 0.3829 - Combined Score: 0.3878 ## 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 | Pearson | Spearmanr | Combined Score | |:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:| | 2.3158 | 1.0 | 90 | 2.7785 | 0.1355 | 0.1181 | 0.1268 | | 2.0193 | 2.0 | 180 | 2.6566 | 0.1954 | 0.2050 | 0.2002 | | 1.7471 | 3.0 | 270 | 2.5202 | 0.2578 | 0.2647 | 0.2612 | | 1.5032 | 4.0 | 360 | 3.0601 | 0.2605 | 0.2732 | 0.2668 | | 1.1825 | 5.0 | 450 | 2.3378 | 0.3150 | 0.3180 | 0.3165 | | 0.8788 | 6.0 | 540 | 2.3657 | 0.3437 | 0.3421 | 0.3429 | | 0.6987 | 7.0 | 630 | 2.0659 | 0.3927 | 0.3829 | 0.3878 | | 0.5879 | 8.0 | 720 | 2.6712 | 0.3631 | 0.3636 | 0.3634 | | 0.4865 | 9.0 | 810 | 2.3066 | 0.3665 | 0.3625 | 0.3645 | | 0.4233 | 10.0 | 900 | 2.2781 | 0.3753 | 0.3695 | 0.3724 | | 0.3628 | 11.0 | 990 | 2.4672 | 0.3848 | 0.3758 | 0.3803 | | 0.3113 | 12.0 | 1080 | 2.4339 | 0.3873 | 0.3809 | 0.3841 | ### Framework versions - Transformers 4.34.0 - Pytorch 1.14.0a0+410ce96 - Datasets 2.14.5 - Tokenizers 0.14.1