This model is a fine-tuned version of gokulsrinivasagan/distilbert_lda_100_v1 on the GLUE WNLI dataset. It achieves the following results on the evaluation set:

Loss: 0.6910
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: 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
0.7643	1.0	3	0.7202	0.4507
0.699	2.0	6	0.6910	0.5634
0.7004	3.0	9	0.6951	0.4789
0.6965	4.0	12	0.6969	0.4366
0.6938	5.0	15	0.7141	0.4507
0.6974	6.0	18	0.7016	0.4366
0.6953	7.0	21	0.7069	0.4366

Framework versions

Transformers 4.46.3
Pytorch 2.2.1+cu118
Datasets 2.17.0
Tokenizers 0.20.3

gokulsrinivasagan/distilbert_lda_100_v1_wnli

distilbert_lda_100_v1_wnli

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

gokulsrinivasagan/
distilbert_lda_100_v1_wnli