--- library_name: transformers license: apache-2.0 base_model: distilbert-base-multilingual-cased tags: - generated_from_trainer metrics: - accuracy model-index: - name: distilbert-base-multilingual-cased-aoe-test3 results: [] --- # distilbert-base-multilingual-cased-aoe-test3 This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.1259 - Accuracy: 0.9563 ## 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: 32 - eval_batch_size: 32 - seed: 42 - 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 - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.1037 | 1.0 | 375 | 0.1388 | 0.954 | | 0.0979 | 2.0 | 750 | 0.1259 | 0.9563 | | 0.0865 | 3.0 | 1125 | 0.1417 | 0.9427 | | 0.0593 | 4.0 | 1500 | 0.1857 | 0.9467 | | 0.0076 | 5.0 | 1875 | 0.2010 | 0.9453 | ### Framework versions - Transformers 4.46.2 - Pytorch 2.5.1+cu121 - Datasets 3.1.0 - Tokenizers 0.20.3