roberta-base-qqp – AI Model by JeremiahZ | AlphaNeural AI

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JeremiahZ/
roberta-base-qqp

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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roberta-base-qqp

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

Loss: 0.4435
Accuracy: 0.9153
F1: 0.8867
Combined Score: 0.9010

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: 2e-05
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.06
num_epochs: 10.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Combined Score
0.2751	1.0	22741	0.3057	0.8905	0.8512	0.8709
0.2443	2.0	45482	0.2530	0.9005	0.8710	0.8857
0.2157	3.0	68223	0.2643	0.9070	0.8769	0.8919
0.1838	4.0	90964	0.2806	0.9109	0.8815	0.8962
0.146	5.0	113705	0.3277	0.9113	0.8809	0.8961
0.1262	6.0	136446	0.3939	0.9113	0.8812	0.8962
0.0867	7.0	159187	0.4435	0.9153	0.8867	0.9010
0.0757	8.0	181928	0.4812	0.9147	0.8844	0.8996
0.0479	9.0	204669	0.5081	0.9151	0.8871	0.9011
0.0379	10.0	227410	0.5647	0.9149	0.8858	0.9003

Framework versions

Transformers 4.20.0.dev0
Pytorch 1.11.0+cu113
Datasets 2.1.0
Tokenizers 0.12.1