| library_name: transformers | |
| license: apache-2.0 | |
| base_model: google-t5/t5-small | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - rouge | |
| model-index: | |
| - name: TokenizerTestingMTSUFall2024SoftwareEngineering | |
| 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. --> | |
| # TokenizerTestingMTSUFall2024SoftwareEngineering | |
| This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on the None dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 1.5198 | |
| - Rouge1: 0.2778 | |
| - Rouge2: 0.2234 | |
| - Rougel: 0.2686 | |
| - Rougelsum: 0.2686 | |
| - Gen Len: 18.9697 | |
| ## 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 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 4 | |
| - mixed_precision_training: Native AMP | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | | |
| |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| | |
| | 1.8333 | 1.0 | 12429 | 1.6354 | 0.2717 | 0.2139 | 0.262 | 0.262 | 18.9751 | | |
| | 1.7368 | 2.0 | 24858 | 1.5610 | 0.2763 | 0.2208 | 0.267 | 0.267 | 18.9735 | | |
| | 1.6978 | 3.0 | 37287 | 1.5291 | 0.2777 | 0.2227 | 0.2683 | 0.2682 | 18.9699 | | |
| | 1.7008 | 4.0 | 49716 | 1.5198 | 0.2778 | 0.2234 | 0.2686 | 0.2686 | 18.9697 | | |
| ### Framework versions | |
| - Transformers 4.44.2 | |
| - Pytorch 2.4.1+cu121 | |
| - Datasets 3.0.1 | |
| - Tokenizers 0.19.1 | |