hBERTv2_data_aug_qqp – AI Model by gokuls | AlphaNeural AI

You can deploy this model and start earning money today!

gokuls/
hBERTv2_data_aug_qqp

like

0

text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

Views

No views yet

hBERTv2_data_aug_qqp

This model is a fine-tuned version of gokuls/bert_12_layer_model_v2 on the GLUE QQP dataset. It achieves the following results on the evaluation set:

Loss: 0.6782
Accuracy: 0.6318
F1: 0.0
Combined Score: 0.3159

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
distributed_type: multi-GPU
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 50
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Combined Score
0.6528	1.0	29671	0.6782	0.6318	0.0	0.3159
0.6407	2.0	59342	nan	0.6318	0.0	0.3159
0.0	3.0	89013	nan	0.6318	0.0	0.3159
0.0	4.0	118684	nan	0.6318	0.0	0.3159
0.0	5.0	148355	nan	0.6318	0.0	0.3159
0.0	6.0	178026	nan	0.6318	0.0	0.3159

Framework versions

Transformers 4.26.1
Pytorch 1.14.0a0+410ce96
Datasets 2.10.1
Tokenizers 0.13.2