metadata
license: mit
base_model: bert-base-german-dbmdz-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: product_classifier_split_url_nodigit_all
results: []
product_classifier_split_url_nodigit_all
This model is a fine-tuned version of bert-base-german-dbmdz-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1833
- Accuracy: 0.9734
- F1: 0.9732
- Precision: 0.9731
- Recall: 0.9734
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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 | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.0385 | 1.0 | 1300 | 0.1880 | 0.9666 | 0.9663 | 0.9665 | 0.9666 |
| 0.0198 | 2.0 | 2600 | 0.1707 | 0.9718 | 0.9718 | 0.9719 | 0.9718 |
| 0.0083 | 3.0 | 3900 | 0.1833 | 0.9734 | 0.9732 | 0.9731 | 0.9734 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3