distilbert_sa_GLUE_Experiment_mrpc_192 – AI Model by gokuls | AlphaNeural AI | AlphaNeural AI

You can deploy this model and start earning money today!

gokuls/
distilbert_sa_GLUE_Experiment_mrpc_192

like

0

text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

Views

No views yet

distilbert_sa_GLUE_Experiment_mrpc_192

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

Loss: 0.5927
Accuracy: 0.6887
F1: 0.7784
Combined Score: 0.7335

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
0.6412	1.0	15	0.6239	0.6838	0.8122	0.7480
0.6281	2.0	30	0.6238	0.6838	0.8122	0.7480
0.629	3.0	45	0.6239	0.6838	0.8122	0.7480
0.6296	4.0	60	0.6236	0.6838	0.8122	0.7480
0.6323	5.0	75	0.6228	0.6838	0.8122	0.7480
0.6272	6.0	90	0.6209	0.6838	0.8122	0.7480
0.6175	7.0	105	0.6000	0.6838	0.8122	0.7480
0.5733	8.0	120	0.5927	0.6887	0.7784	0.7335
0.5199	9.0	135	0.5969	0.6936	0.7818	0.7377
0.4423	10.0	150	0.6369	0.6765	0.7700	0.7233
0.3645	11.0	165	0.6708	0.6838	0.7832	0.7335
0.3203	12.0	180	0.7179	0.6446	0.7249	0.6847
0.2778	13.0	195	0.7517	0.6740	0.7726	0.7233

Framework versions

Transformers 4.26.0
Pytorch 1.14.0a0+410ce96
Datasets 2.8.0
Tokenizers 0.13.2