--- license: apache-2.0 tags: - generated_from_trainer metrics: - accuracy model-index: - name: multiple_answer_QA results: [] --- # multiple_answer_QA This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 5.7334 - Accuracy: 0.2675 ## 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: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 175 | 1.3886 | 0.23 | | No log | 2.0 | 350 | 1.3892 | 0.255 | | 1.3936 | 3.0 | 525 | 1.3863 | 0.2375 | | 1.3936 | 4.0 | 700 | 1.3868 | 0.255 | | 1.3936 | 5.0 | 875 | 1.4511 | 0.26 | | 1.2973 | 6.0 | 1050 | 1.6738 | 0.24 | | 1.2973 | 7.0 | 1225 | 1.9684 | 0.265 | | 1.2973 | 8.0 | 1400 | 2.5002 | 0.28 | | 0.6916 | 9.0 | 1575 | 2.9872 | 0.28 | | 0.6916 | 10.0 | 1750 | 3.2354 | 0.28 | | 0.6916 | 11.0 | 1925 | 3.6618 | 0.3025 | | 0.2428 | 12.0 | 2100 | 4.1750 | 0.275 | | 0.2428 | 13.0 | 2275 | 4.1384 | 0.275 | | 0.2428 | 14.0 | 2450 | 4.5173 | 0.26 | | 0.1118 | 15.0 | 2625 | 4.6013 | 0.275 | | 0.1118 | 16.0 | 2800 | 4.2549 | 0.2525 | | 0.1118 | 17.0 | 2975 | 5.2751 | 0.275 | | 0.0482 | 18.0 | 3150 | 4.9489 | 0.275 | | 0.0482 | 19.0 | 3325 | 5.6077 | 0.28 | | 0.0261 | 20.0 | 3500 | 5.3054 | 0.2625 | | 0.0261 | 21.0 | 3675 | 5.1955 | 0.2625 | | 0.0261 | 22.0 | 3850 | 5.6210 | 0.2575 | | 0.0175 | 23.0 | 4025 | 5.6576 | 0.25 | | 0.0175 | 24.0 | 4200 | 5.6687 | 0.2725 | | 0.0175 | 25.0 | 4375 | 5.6082 | 0.255 | | 0.0133 | 26.0 | 4550 | 5.5999 | 0.27 | | 0.0133 | 27.0 | 4725 | 5.7972 | 0.26 | | 0.0133 | 28.0 | 4900 | 5.6427 | 0.2575 | | 0.0089 | 29.0 | 5075 | 5.7253 | 0.2675 | | 0.0089 | 30.0 | 5250 | 5.7334 | 0.2675 | ### Framework versions - Transformers 4.27.4 - Pytorch 2.0.0+cu118 - Datasets 2.11.0 - Tokenizers 0.13.3