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

Loss: 0.7326
Accuracy: 0.2676

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
0.71	1.0	3	0.7326	0.2676
0.6971	2.0	6	0.7371	0.4366
0.6901	3.0	9	0.7586	0.2394
0.6811	4.0	12	0.7801	0.1549
0.6864	5.0	15	0.7982	0.1690
0.6792	6.0	18	0.8183	0.1690

Framework versions

Transformers 4.46.3
Pytorch 2.2.1+cu118
Datasets 2.17.0
Tokenizers 0.20.3

gokulsrinivasagan/tinybert_train_wnli

tinybert_train_wnli

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

gokulsrinivasagan/
tinybert_train_wnli