--- language: - en base_model: gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48 tags: - generated_from_trainer datasets: - glue metrics: - accuracy model-index: - name: hBERTv1_new_pretrain_w_init_48_ver2_rte results: - task: name: Text Classification type: text-classification dataset: name: GLUE RTE type: glue config: rte split: validation args: rte metrics: - name: Accuracy type: accuracy value: 0.5270758122743683 --- # hBERTv1_new_pretrain_w_init_48_ver2_rte This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48) on the GLUE RTE dataset. It achieves the following results on the evaluation set: - Loss: 0.6919 - Accuracy: 0.5271 ## 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 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.7175 | 1.0 | 39 | 0.6919 | 0.5271 | | 0.7099 | 2.0 | 78 | 0.7006 | 0.4729 | | 0.7111 | 3.0 | 117 | 0.6927 | 0.5271 | | 0.7011 | 4.0 | 156 | 0.6976 | 0.4729 | | 0.7021 | 5.0 | 195 | 0.6955 | 0.4729 | | 0.6986 | 6.0 | 234 | 0.7078 | 0.4729 | ### Framework versions - Transformers 4.34.0 - Pytorch 1.14.0a0+410ce96 - Datasets 2.14.5 - Tokenizers 0.14.1