--- library_name: peft license: apache-2.0 base_model: google-bert/bert-base-multilingual-uncased tags: - generated_from_trainer metrics: - accuracy - f1 - precision - recall model-index: - name: MBERT_uncased_SymmetricCrossEntropy_lora results: [] --- # MBERT_uncased_SymmetricCrossEntropy_lora 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: 0.7435 - Accuracy: 0.711 - F1: 0.8311 - Precision: 0.7204 - Recall: 0.9820 - Roc Auc: 0.4910 ## 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: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 3 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Roc Auc | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-------:| | No log | 0.992 | 31 | 0.7593 | 0.622 | 0.7638 | 0.6975 | 0.8439 | 0.4419 | | No log | 1.984 | 62 | 0.7473 | 0.702 | 0.8249 | 0.7178 | 0.9696 | 0.4848 | | No log | 2.976 | 93 | 0.7435 | 0.711 | 0.8311 | 0.7204 | 0.9820 | 0.4910 | ### Framework versions - PEFT 0.13.3.dev0 - Transformers 4.46.2 - Pytorch 2.5.0+cu121 - Datasets 3.1.0 - Tokenizers 0.20.3