--- license: mit base_model: microsoft/deberta-v3-small tags: - generated_from_trainer metrics: - accuracy - f1 - precision - recall model-index: - name: eng_subcate results: [] --- # eng_subcate This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0837 - Accuracy: 0.0 - F1: 0.0 - Precision: 0.0 - Recall: 0.0 ## 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: 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: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---:|:---------:|:------:| | No log | 1.0 | 53 | 0.3166 | 0.0 | 0.0 | 0.0 | 0.0 | | No log | 2.0 | 106 | 0.1509 | 0.0 | 0.0 | 0.0 | 0.0 | | No log | 3.0 | 159 | 0.1024 | 0.0 | 0.0 | 0.0 | 0.0 | | No log | 4.0 | 212 | 0.0874 | 0.0 | 0.0 | 0.0 | 0.0 | | No log | 5.0 | 265 | 0.0837 | 0.0 | 0.0 | 0.0 | 0.0 | ### Framework versions - Transformers 4.42.4 - Pytorch 2.3.1+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1