--- license: mit base_model: MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: zero-shot_text_classification_fine_tuned results: [] --- # zero-shot_text_classification_fine_tuned This model is a fine-tuned version of [MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli](https://huggingface.co/MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.6389 - Accuracy: 0.8145 - F1: 0.8152 ## 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: 5e-05 - train_batch_size: 16 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - num_epochs: 4 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | No log | 1.0 | 375 | 1.1511 | 0.5755 | 0.5607 | | 1.4974 | 2.0 | 750 | 0.7869 | 0.7535 | 0.7525 | | 0.7908 | 3.0 | 1125 | 0.6635 | 0.8 | 0.8024 | | 0.5067 | 4.0 | 1500 | 0.6389 | 0.8145 | 0.8152 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu121 - Datasets 2.16.1 - Tokenizers 0.15.0