--- library_name: transformers license: apache-2.0 base_model: distilbert-base-multilingual-cased tags: - generated_from_trainer metrics: - accuracy - f1 - precision - recall model-index: - name: results results: [] --- # results This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.8929 - Accuracy: 0.66 - F1: 0.6588 - Precision: 0.6598 - Recall: 0.66 ## 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 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| | 0.8311 | 1.0 | 571 | 0.8145 | 0.6 | 0.6018 | 0.6112 | 0.6 | | 0.5693 | 2.0 | 1142 | 0.8140 | 0.65 | 0.6544 | 0.6676 | 0.65 | | 0.3731 | 3.0 | 1713 | 0.8929 | 0.66 | 0.6588 | 0.6598 | 0.66 | ### Framework versions - Transformers 4.47.1 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0