| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - sciq | |
| metrics: | |
| - accuracy | |
| model-index: | |
| - name: longformer_sciq | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # 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 | |