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Junyi-BERT-sentiment-analysis-IMBD – AI Model by Junyi-Shen | AlphaNeural AI
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Junyi-Shen
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Junyi-BERT-sentiment-analysis-IMBD
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text-classification
en
stanfordnlp/imdb
google-bert/bert-base-uncased
finetune
apache-2.0
us
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Task
Binary sentiment classification (positive / negative)
Source Code
https://github.com/shjy2008/BERT
Training Data
Stage 1: Large-scale sentiment pre-finetuning
Dataset Source:
IMDB Dataset of 50K Movie Reviews
Stage 2: IMDB sentiment fine-tuning
Dataset Source: IMDB sentiment (
https://github.com/acmi-lab/counterfactually-augmented-data/blob/master/sentiment/new/train.tsv
)
Training Method
Loss function: Binary Cross-Entropy (BCE)
Weight decay: 0
Batch size: 8
Dropout: 0.3
Learning rate: 2e-5
Learning rate scheduler: Enabled
Frozen layers: First 9 transformer layers
Evaluation
Test dataset: IMDB sentiment (
https://github.com/acmi-lab/counterfactually-augmented-data/blob/master/sentiment/new/test.tsv
)
Test accuracy:
98.4%
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