--- license: mit tags: - generated_from_trainer metrics: - accuracy base_model: microsoft/deberta-v3-large model-index: - name: deberta-v3-large__sst2__train-16-6 results: [] --- # deberta-v3-large__sst2__train-16-6 This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6846 - Accuracy: 0.5058 ## 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: 4 - eval_batch_size: 4 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 50 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.6673 | 1.0 | 7 | 0.7580 | 0.2857 | | 0.5896 | 2.0 | 14 | 0.7885 | 0.5714 | | 0.5294 | 3.0 | 21 | 1.0040 | 0.4286 | | 0.3163 | 4.0 | 28 | 1.1761 | 0.5714 | | 0.1315 | 5.0 | 35 | 1.4315 | 0.4286 | | 0.0312 | 6.0 | 42 | 2.6115 | 0.2857 | | 0.1774 | 7.0 | 49 | 2.1631 | 0.5714 | | 0.0052 | 8.0 | 56 | 2.3838 | 0.4286 | | 0.0043 | 9.0 | 63 | 2.6553 | 0.4286 | | 0.0032 | 10.0 | 70 | 2.2774 | 0.4286 | | 0.0015 | 11.0 | 77 | 1.9467 | 0.7143 | ### Framework versions - Transformers 4.15.0 - Pytorch 1.10.2+cu102 - Datasets 1.18.2 - Tokenizers 0.10.3