--- language: - en tags: - generated_from_trainer datasets: - glue metrics: - accuracy model-index: - name: hBERTv2_new_pretrain_48_wnli results: - task: name: Text Classification type: text-classification dataset: name: GLUE WNLI type: glue config: wnli split: validation args: wnli metrics: - name: Accuracy type: accuracy value: 0.5633802816901409 --- # hBERTv2_new_pretrain_48_wnli 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 WNLI dataset. It achieves the following results on the evaluation set: - Loss: 0.6839 - Accuracy: 0.5634 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.9503 | 1.0 | 5 | 0.6839 | 0.5634 | | 0.7089 | 2.0 | 10 | 0.6877 | 0.5634 | | 0.7066 | 3.0 | 15 | 0.6858 | 0.5634 | | 0.7051 | 4.0 | 20 | 0.6943 | 0.4789 | | 0.6996 | 5.0 | 25 | 0.7125 | 0.4366 | | 0.7088 | 6.0 | 30 | 0.6890 | 0.5634 | ### Framework versions - Transformers 4.29.2 - Pytorch 1.14.0a0+410ce96 - Datasets 2.12.0 - Tokenizers 0.13.3