--- license: mit base_model: MoritzLaurer/DeBERTa-v3-large-mnli-fever-anli-ling-wanli tags: - generated_from_trainer metrics: - accuracy model-index: - name: 10k-finetune results: [] --- # 10k-finetune This model is a fine-tuned version of [MoritzLaurer/DeBERTa-v3-large-mnli-fever-anli-ling-wanli](https://huggingface.co/MoritzLaurer/DeBERTa-v3-large-mnli-fever-anli-ling-wanli) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.3357 - Accuracy: 0.8730 ## 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-06 - train_batch_size: 2 - eval_batch_size: 16 - seed: 42 - gradient_accumulation_steps: 16 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.06 - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.4093 | 0.33 | 20 | 0.4616 | 0.8115 | | 0.2952 | 0.66 | 40 | 0.3984 | 0.8238 | | 0.2775 | 0.99 | 60 | 0.3357 | 0.8730 | | 0.1836 | 1.32 | 80 | 0.3674 | 0.8402 | | 0.1772 | 1.65 | 100 | 0.3687 | 0.8361 | | 0.1502 | 1.98 | 120 | 0.3730 | 0.8443 | | 0.1245 | 2.31 | 140 | 0.3966 | 0.8402 | | 0.1226 | 2.64 | 160 | 0.3719 | 0.8566 | | 0.1166 | 2.98 | 180 | 0.3768 | 0.8484 | ### Framework versions - Transformers 4.35.0 - Pytorch 2.1.0+cu118 - Datasets 2.14.6 - Tokenizers 0.14.1