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t5-large-billsum
antonkurylo/t5-large-billsum
t5-large-billsum is a summarization model from antonkurylo. Use it when you need a shorter version of a longer text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Summarization
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Oct 23, 2024
- Updated
- Oct 24, 2024
- SHA
- e0461119
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Base models
Model card
From the Hugging Face model README
<!-- 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. -->
t5-large-billsum
This model is a fine-tuned version of t5-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3660
- Rouge1: 54.3212
- Rouge2: 34.3078
- Rougel: 43.7536
- Rougelsum: 47.5193
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 1.6948 | 1.0 | 1250 | 1.4332 | 52.7319 | 33.508 | 42.6688 | 46.3992 |
| 1.4965 | 2.0 | 2500 | 1.3864 | 53.6841 | 33.9189 | 43.3753 | 46.951 |
| 1.4333 | 3.0 | 3750 | 1.3707 | 54.2166 | 34.2285 | 43.5537 | 47.2979 |
| 1.4006 | 4.0 | 5000 | 1.3660 | 54.3212 | 34.3078 | 43.7536 | 47.5193 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1
- Task
- Summarization
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Oct 23, 2024
- Updated
- Oct 24, 2024