--- license: apache-2.0 base_model: google/flan-t5-small tags: - generated_from_trainer model-index: - name: flan-t5-mc-question-generation results: [] inference: parameters: max_length: 512 num_beams: 4 length_penalty: 1.5 no_repeat_ngram_size: 3 early_stopping: True --- # flan-t5-mc-question-generation This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co./google/flan-t5-small) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.2509 ## 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: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 16 - total_train_batch_size: 64 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 7 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 1.9047 | 0.25 | 100 | 1.4246 | | 1.5894 | 0.51 | 200 | 1.3711 | | 1.5355 | 0.76 | 300 | 1.3450 | | 1.5041 | 1.02 | 400 | 1.3255 | | 1.4858 | 1.27 | 500 | 1.3134 | | 1.4711 | 1.53 | 600 | 1.3038 | | 1.4576 | 1.78 | 700 | 1.2951 | | 1.4466 | 2.04 | 800 | 1.2888 | | 1.4405 | 2.29 | 900 | 1.2836 | | 1.4284 | 2.55 | 1000 | 1.2794 | | 1.4228 | 2.8 | 1100 | 1.2758 | | 1.4234 | 3.06 | 1200 | 1.2719 | | 1.4104 | 3.31 | 1300 | 1.2690 | | 1.4147 | 3.56 | 1400 | 1.2666 | | 1.41 | 3.82 | 1500 | 1.2637 | | 1.3996 | 4.07 | 1600 | 1.2622 | | 1.4015 | 4.33 | 1700 | 1.2600 | | 1.3958 | 4.58 | 1800 | 1.2583 | | 1.395 | 4.84 | 1900 | 1.2566 | | 1.3899 | 5.09 | 2000 | 1.2553 | | 1.3929 | 5.35 | 2100 | 1.2542 | | 1.3884 | 5.6 | 2200 | 1.2529 | | 1.3884 | 5.86 | 2300 | 1.2523 | | 1.3821 | 6.11 | 2400 | 1.2520 | | 1.3886 | 6.37 | 2500 | 1.2513 | | 1.3865 | 6.62 | 2600 | 1.2510 | | 1.3841 | 6.87 | 2700 | 1.2509 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.0 - Datasets 2.1.0 - Tokenizers 0.13.3