Jarvisx17

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Average Model Cost: $0.0000

Number of Runs: 6,250

Models by this creator

japanese-sentiment-analysis

japanese-sentiment-analysis

jarvisx17

The "japanese-sentiment-analysis" model is a text classification model that is trained to analyze the sentiment of Japanese sentences. It was specifically trained on the chABSA Japanese dataset using the following hyperparameters: 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, and num_epochs: 10. The model achieved a loss of 0.0001, accuracy of 1.0, and F1 score of 1.0 on the evaluation set. It is intended to be used for sentiment analysis tasks with Japanese text. The model dependencies include fugashi and unidic_lite.

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$-/run

6.1K

Huggingface

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