bert_uncased_L-4_H-256_A-4_rte

This model is a fine-tuned version of google/bert_uncased_L-4_H-256_A-4 on the GLUE RTE dataset. It achieves the following results on the evaluation set:

• Loss: 0.6545
• Accuracy: 0.6318

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
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6982	1.0	10	0.6899	0.5451
0.6864	2.0	20	0.6845	0.5523
0.6733	3.0	30	0.6737	0.5884
0.6495	4.0	40	0.6554	0.5884
0.61	5.0	50	0.6573	0.6101
0.5697	6.0	60	0.6545	0.6318
0.5279	7.0	70	0.6648	0.6354
0.4859	8.0	80	0.6778	0.6173
0.4524	9.0	90	0.6933	0.6137
0.4126	10.0	100	0.6992	0.6245
0.386	11.0	110	0.7181	0.6426

Framework versions

• Transformers 4.46.3
• Pytorch 2.2.1+cu118
• Datasets 2.17.0
• Tokenizers 0.20.3