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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: google-t5/t5-small |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: MTSUSpring2025SoftwareEngineering |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# MTSUSpring2025SoftwareEngineering |
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This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4609 |
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- Rouge1: 0.2922 |
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- Rouge2: 0.2362 |
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- Rougel: 0.282 |
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- Rougelsum: 0.282 |
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- Gen Len: 19.951 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 6 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
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| 1.8149 | 1.0 | 12429 | 1.6198 | 0.2838 | 0.2222 | 0.2726 | 0.2726 | 19.9612 | |
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| 1.7131 | 2.0 | 24858 | 1.5410 | 0.2874 | 0.2291 | 0.2768 | 0.2767 | 19.9596 | |
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| 1.6671 | 3.0 | 37287 | 1.5011 | 0.2892 | 0.2316 | 0.2787 | 0.2787 | 19.9572 | |
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| 1.6542 | 4.0 | 49716 | 1.4750 | 0.291 | 0.2349 | 0.2809 | 0.2808 | 19.9496 | |
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| 1.6116 | 5.0 | 62145 | 1.4636 | 0.292 | 0.236 | 0.2818 | 0.2818 | 19.9516 | |
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| 1.6247 | 6.0 | 74574 | 1.4609 | 0.2922 | 0.2362 | 0.282 | 0.282 | 19.951 | |
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### Framework versions |
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- Transformers 4.48.3 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.3.2 |
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- Tokenizers 0.21.0 |
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