--- license: apache-2.0 base_model: bert-base-multilingual-uncased tags: - generated_from_trainer metrics: - accuracy - recall - precision model-index: - name: multilingual_model_v02 results: [] --- # multilingual_model_v02 This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.3359 - Accuracy: 0.8707 - F1 Score: 0.7728 - Recall: 0.8527 - Precision: 0.7066 ## 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: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | Recall | Precision | |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------:|:---------:| | No log | 1.0 | 219 | 0.3391 | 0.8707 | 0.7728 | 0.8527 | 0.7066 | | No log | 2.0 | 438 | 0.3377 | 0.8707 | 0.7728 | 0.8527 | 0.7066 | | 0.3688 | 3.0 | 657 | 0.3359 | 0.8707 | 0.7728 | 0.8527 | 0.7066 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.3.0+cu121 - Datasets 2.19.2 - Tokenizers 0.19.1