--- license: apache-2.0 tags: - text-classification - generated_from_trainer datasets: - xnli metrics: - accuracy model-index: - name: xnli_m_bert_only_de results: - task: name: Text Classification type: text-classification dataset: name: xnli type: xnli config: de split: train args: de metrics: - name: Accuracy type: accuracy value: 0.7562248995983936 --- # xnli_m_bert_only_de This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the xnli dataset. It achieves the following results on the evaluation set: - Loss: 1.1207 - Accuracy: 0.7562 ## 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: 5e-05 - train_batch_size: 128 - eval_batch_size: 128 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 1 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.1041 | 1.0 | 3068 | 1.1207 | 0.7562 | ### Framework versions - Transformers 4.24.0 - Pytorch 1.13.0 - Datasets 2.6.1 - Tokenizers 0.13.1