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t5-small-finetuned-xsum
jgoodie/t5-small-finetuned-xsum
t5-small-finetuned-xsum is a machine learning model from jgoodie. 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.
should 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 1, 2023
- Updated
- Jan 1, 2023
- SHA
- cfa55869
Datasets
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-small-finetuned-xsum
This model is a fine-tuned version of t5-small on the xsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.4768
- Rouge1: 28.5758
- Rouge2: 7.9219
- Rougel: 22.5161
- Rougelsum: 22.5215
- Gen Len: 18.8288
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.7504 | 1.0 | 6377 | 2.5012 | 28.218 | 7.6611 | 22.1733 | 22.1702 | 18.8299 |
| 2.7148 | 2.0 | 12754 | 2.4768 | 28.5758 | 7.9219 | 22.5161 | 22.5215 | 18.8288 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Jan 1, 2023
- Updated
- Jan 1, 2023