distilbert-mrpc – AI Model by mattchurgin | AlphaNeural AI

You can deploy this model and start earning money today!

mattchurgin/
distilbert-mrpc

like

0

text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

Views

No views yet

distilbert-mrpc

This model is a fine-tuned version of distilbert-base-uncased on the glue dataset. It achieves the following results on the evaluation set:

Loss: 0.6783
Accuracy: 0.8480
F1: 0.8935

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.5916	0.22	100	0.5676	0.7157	0.8034
0.5229	0.44	200	0.4534	0.7770	0.8212
0.5055	0.65	300	0.4037	0.8137	0.8762
0.4597	0.87	400	0.3706	0.8407	0.8893
0.4	1.09	500	0.4590	0.8113	0.8566
0.3498	1.31	600	0.4196	0.8554	0.8974
0.2916	1.53	700	0.4606	0.8554	0.8933
0.3309	1.74	800	0.5162	0.8578	0.9027
0.3788	1.96	900	0.3911	0.8529	0.8980
0.2059	2.18	1000	0.5842	0.8554	0.8995
0.1595	2.4	1100	0.5701	0.8578	0.8975
0.1205	2.61	1200	0.6905	0.8407	0.8889
0.174	2.83	1300	0.6783	0.8480	0.8935

Framework versions

Transformers 4.15.0
Pytorch 1.10.1
Datasets 1.17.0
Tokenizers 0.10.3