NL_BERT_michelin_finetuned
This model is a fine-tuned version of GroNLP/bert-base-dutch-cased on a Dutch restaurant reviews dataset. Provide Dutch review text to the API on the right and receive a score that indicates whether this restaurant is eligible for a Michelin star ;) It achieves the following results on the evaluation set:
- Loss: 0.0637
- Accuracy: 0.9836
- Recall: 0.5486
- Precision: 0.7914
- F1: 0.6480
- Mse: 0.0164
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: 32
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision | F1 | Mse |
|---|---|---|---|---|---|---|---|---|
| 0.1043 | 1.0 | 3647 | 0.0961 | 0.9792 | 0.3566 | 0.7606 | 0.4856 | 0.0208 |
| 0.0799 | 2.0 | 7294 | 0.0797 | 0.9803 | 0.4364 | 0.7415 | 0.5495 | 0.0197 |
| 0.0589 | 3.0 | 10941 | 0.0637 | 0.9836 | 0.5486 | 0.7914 | 0.6480 | 0.0164 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1
- Downloads last month
- 17
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.