--- language: - en tags: - generated_from_trainer datasets: - glue metrics: - accuracy model-index: - name: hBERTv2_new_pretrain_48_qnli results: - task: name: Text Classification type: text-classification dataset: name: GLUE QNLI type: glue config: qnli split: validation args: qnli metrics: - name: Accuracy type: accuracy value: 0.5967417170053084 --- # hBERTv2_new_pretrain_48_qnli 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 QNLI dataset. It achieves the following results on the evaluation set: - Loss: 0.6635 - Accuracy: 0.5967 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.6834 | 1.0 | 819 | 0.6635 | 0.5967 | | 0.6634 | 2.0 | 1638 | 0.6696 | 0.5931 | | 0.6597 | 3.0 | 2457 | 0.6701 | 0.6013 | | 0.6607 | 4.0 | 3276 | 0.6780 | 0.5876 | | 0.6602 | 5.0 | 4095 | 0.6903 | 0.5858 | | 0.6577 | 6.0 | 4914 | 0.6712 | 0.5892 | ### Framework versions - Transformers 4.29.2 - Pytorch 1.14.0a0+410ce96 - Datasets 2.12.0 - Tokenizers 0.13.3