--- library_name: transformers license: apache-2.0 base_model: Alibaba-NLP/gte-multilingual-reranker-base tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: ModernBERT-Letter results: [] --- # ModernBERT-Letter This model is a fine-tuned version of [Alibaba-NLP/gte-multilingual-reranker-base](https://huggingface.co/Alibaba-NLP/gte-multilingual-reranker-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0038 - Accuracy: 1.0 - F1: 1.0 ## 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: 3e-06 - train_batch_size: 16 - eval_batch_size: 64 - 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: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | No log | 1.0 | 161 | 0.4207 | 0.9580 | 0.9554 | | No log | 2.0 | 322 | 0.0516 | 0.9965 | 0.9964 | | No log | 3.0 | 483 | 0.0187 | 1.0 | 1.0 | | 0.391 | 4.0 | 644 | 0.0104 | 1.0 | 1.0 | | 0.391 | 5.0 | 805 | 0.0072 | 1.0 | 1.0 | | 0.391 | 6.0 | 966 | 0.0056 | 1.0 | 1.0 | | 0.0145 | 7.0 | 1127 | 0.0047 | 1.0 | 1.0 | | 0.0145 | 8.0 | 1288 | 0.0042 | 1.0 | 1.0 | | 0.0145 | 9.0 | 1449 | 0.0039 | 1.0 | 1.0 | | 0.0079 | 10.0 | 1610 | 0.0038 | 1.0 | 1.0 | ### Framework versions - Transformers 4.47.0 - Pytorch 2.5.1+cu121 - Datasets 3.3.1 - Tokenizers 0.21.0