| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: google-t5/t5-small |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - rouge |
| | model-index: |
| | - name: MTSUSpring2025SoftwareEngineering |
| | 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. --> |
| |
|
| | # MTSUSpring2025SoftwareEngineering |
| |
|
| | 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: 1.5063 |
| | - Rouge1: 0.0879 |
| | - Rouge2: 0.0695 |
| | - Rougel: 0.0847 |
| | - Rougelsum: 0.0847 |
| | - Gen Len: 7.2123 |
| |
|
| | ## 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: 1e-05 |
| | - train_batch_size: 4 |
| | - eval_batch_size: 4 |
| | - seed: 42 |
| | - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: linear |
| | - num_epochs: 5 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| | |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
| | | 1.8535 | 1.0 | 14778 | 1.6426 | 0.0806 | 0.063 | 0.0776 | 0.0776 | 6.8024 | |
| | | 1.7555 | 2.0 | 29556 | 1.5664 | 0.0839 | 0.0658 | 0.0808 | 0.0808 | 7.0022 | |
| | | 1.7044 | 3.0 | 44334 | 1.5297 | 0.086 | 0.0676 | 0.0828 | 0.0828 | 7.1049 | |
| | | 1.7096 | 4.0 | 59112 | 1.5119 | 0.0875 | 0.0692 | 0.0843 | 0.0843 | 7.186 | |
| | | 1.6789 | 5.0 | 73890 | 1.5063 | 0.0879 | 0.0695 | 0.0847 | 0.0847 | 7.2123 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.49.0 |
| | - Pytorch 2.6.0+cu124 |
| | - Datasets 3.4.1 |
| | - Tokenizers 0.21.1 |
| |
|
