tiny_bert_rand_50_v1_wnli

This model is a fine-tuned version of Hartunka/tiny_bert_rand_50_v1 on the GLUE WNLI dataset. It achieves the following results on the evaluation set:

• Loss: 0.6924
• 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: 5e-05
• train_batch_size: 256
• eval_batch_size: 256
• seed: 10
• 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
0.6996	1.0	3	0.6930	0.5352
0.6965	2.0	6	0.6924	0.5634
0.6961	3.0	9	0.7065	0.3662
0.6933	4.0	12	0.7048	0.3521
0.6941	5.0	15	0.7031	0.4507
0.6911	6.0	18	0.7073	0.3944
0.6905	7.0	21	0.7102	0.4085

Framework versions

• Transformers 4.40.0
• Pytorch 2.6.0+cu124
• Datasets 3.5.0
• Tokenizers 0.19.1