hBERTv2_new_pretrain_48_wnli

This model is a fine-tuned version of 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