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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: TennesseeLegislationBillSummarizer |
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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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# TennesseeLegislationBillSummarizer |
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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: 0.9419 |
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- Rouge1: 0.5247 |
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- Rouge2: 0.4182 |
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- Rougel: 0.4983 |
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- Rougelsum: 0.4983 |
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- Gen Len: 19.714 |
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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_FUSED 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: 5 |
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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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| 1.1552 | 1.0 | 15881 | 1.0253 | 0.5162 | 0.4064 | 0.4892 | 0.4892 | 19.7538 | |
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| 1.0885 | 2.0 | 31762 | 0.9789 | 0.5182 | 0.4099 | 0.4919 | 0.4918 | 19.7598 | |
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| 1.051 | 3.0 | 47643 | 0.9575 | 0.5211 | 0.4136 | 0.4948 | 0.4948 | 19.7535 | |
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| 1.0578 | 4.0 | 63524 | 0.9457 | 0.5237 | 0.4168 | 0.4973 | 0.4973 | 19.7212 | |
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| 1.0285 | 5.0 | 79405 | 0.9419 | 0.5247 | 0.4182 | 0.4983 | 0.4983 | 19.714 | |
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### Framework versions |
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- Transformers 4.57.1 |
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- Pytorch 2.8.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.22.1 |
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