File size: 1,647 Bytes
14060e9 a63cb67 14060e9 a63cb67 14060e9 a63cb67 14060e9 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 |
---
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: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# jp-speech-classifier
This model is a fine-tuned version of [cl-tohoku/bert-base-japanese-v3](https://huggingface.co/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
|