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summarization-t5-small-finetuned-billsum
raj-p/summarization-t5-small-finetuned-billsum
summarization-t5-small-finetuned-billsum is a machine learning model from raj-p. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Jan 19, 2024
- Updated
- Jan 19, 2024
- SHA
- 97da8737
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
raj-p/summarization-t5-small-finetuned-billsum
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 2.5527
- Validation Loss: 2.3306
- Epoch: 2
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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
Training results
| Train Loss | Validation Loss | Epoch |
|---|---|---|
| 3.1611 | 2.5585 | 0 |
| 2.6854 | 2.4063 | 1 |
| 2.5527 | 2.3306 | 2 |
Framework versions
- Transformers 4.35.2
- TensorFlow 2.15.0
- Datasets 2.16.1
- Tokenizers 0.15.0
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Jan 19, 2024
- Updated
- Jan 19, 2024