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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: 1.2226 |
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- Rouge1: 0.0823 |
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- Rouge2: 0.0672 |
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- Rougel: 0.0799 |
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- Rougelsum: 0.0798 |
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- Gen Len: 6.8086 |
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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: 5e-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: 8 |
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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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| 1.6211 | 1.0 | 14778 | 1.4386 | 0.086 | 0.0686 | 0.0831 | 0.0831 | 7.0473 | |
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| 1.5116 | 2.0 | 29556 | 1.3540 | 0.0836 | 0.0677 | 0.0811 | 0.0811 | 6.9131 | |
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| 1.4459 | 3.0 | 44334 | 1.3019 | 0.0874 | 0.0708 | 0.0847 | 0.0846 | 7.1384 | |
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| 1.42 | 4.0 | 59112 | 1.2729 | 0.0843 | 0.0687 | 0.0818 | 0.0817 | 6.9433 | |
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| 1.3683 | 5.0 | 73890 | 1.2490 | 0.0838 | 0.0684 | 0.0814 | 0.0812 | 6.916 | |
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| 1.3589 | 6.0 | 88668 | 1.2357 | 0.0847 | 0.0692 | 0.0822 | 0.0821 | 6.995 | |
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| 1.353 | 7.0 | 103446 | 1.2245 | 0.0825 | 0.0673 | 0.08 | 0.0799 | 6.8302 | |
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| 1.3506 | 8.0 | 118224 | 1.2226 | 0.0823 | 0.0672 | 0.0799 | 0.0798 | 6.8086 | |
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### Framework versions |
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- Transformers 4.49.0 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.4.1 |
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- Tokenizers 0.21.1 |
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