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

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JeremiahZ/
roberta-base-stsb

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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roberta-base-stsb

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

Loss: 0.4155
Pearson: 0.9101
Spearmanr: 0.9079
Combined Score: 0.9090

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	Pearson	Spearmanr	Combined Score
No log	1.0	360	0.6202	0.8787	0.8813	0.8800
1.6425	2.0	720	0.4864	0.9008	0.8992	0.9000
0.3629	3.0	1080	0.4201	0.9043	0.9016	0.9030
0.3629	4.0	1440	0.4686	0.9052	0.9003	0.9027
0.2212	5.0	1800	0.4622	0.9061	0.9031	0.9046
0.1556	6.0	2160	0.3952	0.9086	0.9065	0.9075
0.1162	7.0	2520	0.4271	0.9081	0.9070	0.9075
0.1162	8.0	2880	0.4169	0.9094	0.9075	0.9085
0.0887	9.0	3240	0.4383	0.9091	0.9074	0.9083
0.0717	10.0	3600	0.4155	0.9101	0.9079	0.9090

Framework versions

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