--- license: apache-2.0 base_model: google-bert/bert-base-multilingual-uncased tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: bert-base-multilingual-uncased-finetuned-ner-harem results: [] --- # bert-base-multilingual-uncased-finetuned-ner-harem This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.1861 - Precision: 0.7833 - Recall: 0.7589 - F1: 0.7709 - Accuracy: 0.9634 ## 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: 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: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | No log | 1.0 | 282 | 0.2275 | 0.5847 | 0.6014 | 0.5929 | 0.9378 | | 0.2687 | 2.0 | 564 | 0.1620 | 0.7389 | 0.6754 | 0.7057 | 0.9583 | | 0.2687 | 3.0 | 846 | 0.1395 | 0.7820 | 0.7446 | 0.7628 | 0.9659 | | 0.0845 | 4.0 | 1128 | 0.1694 | 0.7458 | 0.7351 | 0.7404 | 0.9586 | | 0.0845 | 5.0 | 1410 | 0.1861 | 0.7833 | 0.7589 | 0.7709 | 0.9634 | | 0.0398 | 6.0 | 1692 | 0.1821 | 0.7583 | 0.7637 | 0.7610 | 0.9639 | | 0.0398 | 7.0 | 1974 | 0.2303 | 0.7789 | 0.7064 | 0.7409 | 0.9595 | | 0.0203 | 8.0 | 2256 | 0.1912 | 0.7350 | 0.7876 | 0.7604 | 0.9629 | | 0.0109 | 9.0 | 2538 | 0.2304 | 0.7524 | 0.7613 | 0.7568 | 0.9595 | | 0.0109 | 10.0 | 2820 | 0.2457 | 0.7617 | 0.7399 | 0.7506 | 0.9622 | ### Framework versions - Transformers 4.41.1 - Pytorch 2.1.2 - Datasets 2.19.1 - Tokenizers 0.19.1