--- license: mit base_model: microsoft/deberta-v3-xsmall tags: - generated_from_trainer metrics: - accuracy model-index: - name: STS-Conventional-Fine-Tuning results: [] --- # STS-Conventional-Fine-Tuning This model is a fine-tuned version of [microsoft/deberta-v3-xsmall](https://huggingface.co/microsoft/deberta-v3-xsmall) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.7499 - Accuracy: 0.2429 ## 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: 0.03 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 180 | 1.7520 | 0.2429 | | No log | 2.0 | 360 | 1.7483 | 0.2429 | | 3.3637 | 3.0 | 540 | 1.7498 | 0.2429 | | 3.3637 | 4.0 | 720 | 1.7525 | 0.2429 | | 3.3637 | 5.0 | 900 | 1.7499 | 0.2429 | ### Framework versions - Transformers 4.38.2 - Pytorch 2.2.1+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2