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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: TX_Legislature_Summarizer |
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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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# TX_Legislature_Summarizer |
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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: 0.0804 |
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- Rouge1: 0.8765 |
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- Rouge2: 0.8513 |
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- Rougel: 0.872 |
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- Rougelsum: 0.8719 |
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- Gen Len: 18.3293 |
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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: 2 |
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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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| 0.105 | 1.0 | 18155 | 0.0862 | 0.874 | 0.8477 | 0.8694 | 0.8693 | 18.3724 | |
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| 0.0852 | 2.0 | 36310 | 0.0804 | 0.8765 | 0.8513 | 0.872 | 0.8719 | 18.3293 | |
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### Framework versions |
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- Transformers 4.57.2 |
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- Pytorch 2.9.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.22.1 |
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