--- license: mit base_model: MoritzLaurer/deberta-v3-large-zeroshot-v2.0 tags: - generated_from_trainer metrics: - accuracy model-index: - name: fine-tuned-MoritzLaurer-deberta-v3-large-zeroshot-v2.0-arceasy results: [] --- # fine-tuned-MoritzLaurer-deberta-v3-large-zeroshot-v2.0-arceasy This model is a fine-tuned version of [MoritzLaurer/deberta-v3-large-zeroshot-v2.0](https://huggingface.co/MoritzLaurer/deberta-v3-large-zeroshot-v2.0) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.8204 - Accuracy: 0.8175 ## 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: 1.5e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 6 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 141 | 0.4636 | 0.8333 | | No log | 2.0 | 282 | 0.5887 | 0.8175 | | No log | 3.0 | 423 | 0.5583 | 0.8316 | | 0.3291 | 4.0 | 564 | 0.7024 | 0.8246 | | 0.3291 | 5.0 | 705 | 0.7975 | 0.8246 | | 0.3291 | 6.0 | 846 | 0.8204 | 0.8175 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.3.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1