--- license: apache-2.0 base_model: bert-base-multilingual-uncased tags: - generated_from_trainer metrics: - accuracy - f1 - precision - recall model-index: - name: product_classifier_split_url_nodigit_lv results: [] --- # product_classifier_split_url_nodigit_lv This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.1212 - Accuracy: 0.9747 - F1: 0.9745 - Precision: 0.9745 - Recall: 0.9747 ## 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: 4 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| | 0.1798 | 1.0 | 1085 | 0.1438 | 0.9556 | 0.9556 | 0.9558 | 0.9556 | | 0.1004 | 2.0 | 2170 | 0.1257 | 0.9688 | 0.9687 | 0.9687 | 0.9688 | | 0.0673 | 3.0 | 3255 | 0.1175 | 0.9742 | 0.9741 | 0.9741 | 0.9742 | | 0.037 | 4.0 | 4340 | 0.1212 | 0.9747 | 0.9745 | 0.9745 | 0.9747 | ### Framework versions - Transformers 4.32.0 - Pytorch 2.0.1+cu117 - Datasets 2.14.4 - Tokenizers 0.13.3