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

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JeremiahZ/
roberta-base-qnli

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text-classification

generated_from_trainer

FacebookAI/roberta-base

autotrain_compatible

endpoints_compatible

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roberta-base-qnli

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

Loss: 0.2992
Accuracy: 0.9246

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
0.2986	1.0	6547	0.2215	0.9171
0.243	2.0	13094	0.2321	0.9173
0.2048	3.0	19641	0.2992	0.9246
0.1629	4.0	26188	0.3538	0.9220
0.1308	5.0	32735	0.3533	0.9209
0.0846	6.0	39282	0.4277	0.9229

Framework versions

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