--- license: apache-2.0 base_model: google-bert/bert-base-multilingual-uncased tags: - generated_from_trainer metrics: - accuracy - precision - recall - f1 model-index: - name: result-colab results: [] --- # result-colab 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: 0.4210 - Accuracy: 0.9083 - Precision: 0.9076 - Recall: 0.9099 - F1: 0.9085 ## 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: 1e-05 - train_batch_size: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - num_epochs: 8 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| | 0.11 | 1.0 | 24 | 0.4032 | 0.8991 | 0.9040 | 0.8991 | 0.8980 | | 0.0824 | 2.0 | 48 | 0.4500 | 0.8853 | 0.8806 | 0.8874 | 0.8810 | | 0.0901 | 3.0 | 72 | 0.4908 | 0.8716 | 0.8809 | 0.8576 | 0.8653 | | 0.0554 | 4.0 | 96 | 0.4473 | 0.8991 | 0.9059 | 0.8943 | 0.8984 | | 0.0612 | 5.0 | 120 | 0.4675 | 0.8807 | 0.8867 | 0.8723 | 0.8766 | | 0.0508 | 6.0 | 144 | 0.4011 | 0.9220 | 0.9228 | 0.9191 | 0.9203 | | 0.0513 | 7.0 | 168 | 0.4161 | 0.9083 | 0.9049 | 0.9098 | 0.9070 | | 0.049 | 8.0 | 192 | 0.4210 | 0.9083 | 0.9076 | 0.9099 | 0.9085 | ### Framework versions - Transformers 4.42.4 - Pytorch 2.3.1+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1