hBERTv2_rte

This model is a fine-tuned version of gokuls/bert_12_layer_model_v2 on the GLUE RTE dataset. It achieves the following results on the evaluation set:

• Loss: 0.6896
• Accuracy: 0.5487

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: 5e-05
• train_batch_size: 256
• eval_batch_size: 256
• 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
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.7231	1.0	10	0.7175	0.4549
0.702	2.0	20	0.7053	0.4729
0.6982	3.0	30	0.6976	0.4585
0.7008	4.0	40	0.7261	0.4657
0.7022	5.0	50	0.7142	0.4946
0.6867	6.0	60	0.6943	0.4801
0.6796	7.0	70	0.6896	0.5487
0.6614	8.0	80	0.7151	0.5162
0.6303	9.0	90	0.7244	0.5271
0.602	10.0	100	0.7570	0.4729
0.5761	11.0	110	0.7605	0.5379
0.5664	12.0	120	0.8160	0.5235

Framework versions

• Transformers 4.26.1
• Pytorch 1.14.0a0+410ce96
• Datasets 2.10.1
• Tokenizers 0.13.2