--- 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-geocorpus results: [] --- # bert-base-multilingual-uncased-finetuned-ner-geocorpus 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: 0.1137 - Precision: 0.8040 - Recall: 0.7863 - F1: 0.7951 - Accuracy: 0.9678 ## 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 | 276 | 0.1781 | 0.6711 | 0.6469 | 0.6588 | 0.9541 | | 0.2543 | 2.0 | 552 | 0.1287 | 0.7567 | 0.7875 | 0.7718 | 0.9638 | | 0.2543 | 3.0 | 828 | 0.1137 | 0.8040 | 0.7863 | 0.7951 | 0.9678 | | 0.0868 | 4.0 | 1104 | 0.1205 | 0.7628 | 0.8630 | 0.8098 | 0.9674 | | 0.0868 | 5.0 | 1380 | 0.1184 | 0.8093 | 0.8722 | 0.8396 | 0.9722 | | 0.0448 | 6.0 | 1656 | 0.1148 | 0.7817 | 0.8943 | 0.8342 | 0.9723 | ### Framework versions - Transformers 4.41.1 - Pytorch 2.1.2 - Datasets 2.19.1 - Tokenizers 0.19.1