--- tags: - generated_from_trainer datasets: - sciq metrics: - accuracy model-index: - name: longformer_sciq results: [] --- # longformer_sciq This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co/allenai/longformer-base-4096) on the sciq dataset. It achieves the following results on the evaluation set: - Loss: 0.1479 - Accuracy: 0.932 ## 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: 2 - eval_batch_size: 2 - seed: 42 - gradient_accumulation_steps: 25 - total_train_batch_size: 50 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 233 | 0.1650 | 0.934 | | No log | 2.0 | 466 | 0.1479 | 0.932 | ### Framework versions - Transformers 4.21.3 - Pytorch 1.12.1 - Datasets 2.5.1 - Tokenizers 0.11.0