--- library_name: transformers license: apache-2.0 base_model: ltg/nort5-base tags: - generated_from_trainer model-index: - name: ltg_nort5-base results: [] --- # ltg_nort5-base This model is a fine-tuned version of [ltg/nort5-base](https://huggingface.co/ltg/nort5-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.1309 ## 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: 0.0003 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - 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: cosine - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 10 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:------:|:----:|:---------------:| | 0.799 | 0.1953 | 100 | 0.7628 | | 0.1798 | 0.3906 | 200 | 0.1886 | | 0.3739 | 0.5859 | 300 | 0.3134 | | 0.159 | 0.7812 | 400 | 0.1574 | | 0.132 | 0.9766 | 500 | 0.1451 | | 0.1338 | 1.1719 | 600 | 0.1335 | | 0.1412 | 1.3672 | 700 | 0.1309 | | 0.1335 | 1.5625 | 800 | 0.1336 | ### Framework versions - Transformers 4.51.3 - Pytorch 2.7.0+cu118 - Datasets 3.5.1 - Tokenizers 0.21.1