This model is a fine-tuned version of google/bert_uncased_L-4_H-128_A-2 on the GLUE WNLI dataset. It achieves the following results on the evaluation set:

Loss: 0.7042
Accuracy: 0.3521

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
0.6968	1.0	3	0.7060	0.4225
0.6898	2.0	6	0.7042	0.3521
0.6912	3.0	9	0.7055	0.3662
0.695	4.0	12	0.7075	0.3380
0.6946	5.0	15	0.7099	0.3099
0.6921	6.0	18	0.7122	0.3099
0.6874	7.0	21	0.7140	0.3239

Framework versions

Transformers 4.46.3
Pytorch 2.2.1+cu118
Datasets 2.17.0
Tokenizers 0.20.3

gokulsrinivasagan/bert_uncased_L-4_H-128_A-2_wnli

bert_uncased_L-4_H-128_A-2_wnli

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

gokulsrinivasagan/
bert_uncased_L-4_H-128_A-2_wnli