--- license: apache-2.0 base_model: allenai/longformer-base-4096 tags: - generated_from_trainer datasets: - imdb metrics: - accuracy model-index: - name: my_awesome_model results: - task: name: Text Classification type: text-classification dataset: name: imdb type: imdb config: plain_text split: test args: plain_text metrics: - name: Accuracy type: accuracy value: 0.95528 --- # my_awesome_model This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co./allenai/longformer-base-4096) on the imdb dataset. It achieves the following results on the evaluation set: - Loss: 0.2141 - Accuracy: 0.9553 ## 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: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 8 - 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.3358 | 0.32 | 1000 | 0.2286 | 0.9349 | | 0.2658 | 0.64 | 2000 | 0.2036 | 0.9447 | | 0.2392 | 0.96 | 3000 | 0.2294 | 0.9504 | | 0.1648 | 1.28 | 4000 | 0.2288 | 0.9518 | | 0.1477 | 1.6 | 5000 | 0.2190 | 0.9532 | | 0.1404 | 1.92 | 6000 | 0.2141 | 0.9553 | ### Framework versions - Transformers 4.35.0 - Pytorch 2.1.0+cu118 - Datasets 2.14.6 - Tokenizers 0.14.1