--- license: apache-2.0 base_model: mnaylor/mega-base-wikitext tags: - generated_from_trainer metrics: - accuracy - precision - recall - f1 model-index: - name: mega-base-multiple-choice-fp16-v3 results: [] --- # mega-base-multiple-choice-fp16-v3 This model is a fine-tuned version of [mnaylor/mega-base-wikitext](https://huggingface.co/mnaylor/mega-base-wikitext) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6932 - Accuracy: 0.4974 - Precision: 0.4974 - Recall: 0.5020 - F1: 0.4997 ## 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: 1024 - eval_batch_size: 1024 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 24000 - num_epochs: 3 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| | No log | 1.0 | 34 | 0.6932 | 0.4970 | 0.4971 | 0.5023 | 0.4997 | | No log | 2.0 | 68 | 0.6932 | 0.4975 | 0.4975 | 0.5026 | 0.5001 | | No log | 3.0 | 102 | 0.6932 | 0.4974 | 0.4974 | 0.5020 | 0.4997 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu121 - Datasets 2.16.1 - Tokenizers 0.15.0