test_trainer
This model is a fine-tuned version of cl-tohoku/bert-base-japanese-v3 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3337
- Accuracy: 0.9261
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 399 | 0.2528 | 0.9135 |
| 0.3478 | 2.0 | 798 | 0.2996 | 0.9261 |
| 0.2034 | 3.0 | 1197 | 0.3337 | 0.9261 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1
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Inference Providers
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Model tree for michamcs/bert-japanese-food-classification
Base model
tohoku-nlp/bert-base-japanese-v3