--- license: mit tags: - generated_from_trainer metrics: - accuracy base_model: microsoft/deberta-v3-large model-index: - name: deberta-v3-large__sst2__train-8-0 results: [] --- # deberta-v3-large__sst2__train-8-0 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: 0.7088 - Accuracy: 0.5008 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.6705 | 1.0 | 3 | 0.7961 | 0.25 | | 0.6571 | 2.0 | 6 | 0.8092 | 0.25 | | 0.7043 | 3.0 | 9 | 0.7977 | 0.25 | | 0.6207 | 4.0 | 12 | 0.8478 | 0.25 | | 0.5181 | 5.0 | 15 | 0.9782 | 0.25 | | 0.4136 | 6.0 | 18 | 1.3151 | 0.25 | | 0.3702 | 7.0 | 21 | 1.8633 | 0.25 | | 0.338 | 8.0 | 24 | 2.2119 | 0.25 | | 0.2812 | 9.0 | 27 | 2.3058 | 0.25 | | 0.2563 | 10.0 | 30 | 2.3353 | 0.25 | | 0.2132 | 11.0 | 33 | 2.5921 | 0.25 | ### Framework versions - Transformers 4.15.0 - Pytorch 1.10.2+cu102 - Datasets 1.18.2 - Tokenizers 0.10.3