japanese sentiment analysis This model was trained from scratch on the chABSA dataset. It achieves the following results on the evaluation set: Loss: 0.0001 Accuracy: 1.0 F1: 1.0 Model description Model Train for Japanese sentence sentiments. Intended uses & limitations The model was trained on chABSA Japanese dataset. DATASET link : https://www.kaggle.com/datasets/takahirokubo0/chabsa Training hyperparameters The following hyperparameters were used during training: learning rate: 2e 05 train batch size: 16 eval batch size: 16 seed: 42 optimizer: Adam with betas=(0.9,0.999) and epsilon=1e 08 lr scheduler type: linear num epochs: 10 Usage You can use cURL to access this model: Python API: Training results Framework versions Transformers 4.24.0 Pytorch 1.12.1+cu113 Datasets 2.7.0 Tokenizers 0.13.2 Dependencies !pip install fugashi !pip install unidic lite
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