metadata
license: apache-2.0
base_model: cl-tohoku/bert-base-japanese-v3
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: jp-speech-classifier
results: []
jp-speech-classifier
This model is a fine-tuned version of cl-tohoku/bert-base-japanese-v3 on a dataset created from speech records in the Japanese diet. It achieves the following results on the evaluation set:
- Loss: 1.1895
- Accuracy: 0.7053
Model description
This model classifies Japanese sentences into factual, question, descriptive, opinion based and other sentences.
Intended uses & limitations
This model can be used for any purpose that requires sentence categorization of Japanese sentences. The dataset is fairly small but it gets the job done.
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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 72 | 1.1048 | 0.6772 |
| No log | 2.0 | 144 | 1.1895 | 0.7053 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3