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t5-small-finetuned-xsum
hientptran/t5-small-finetuned-xsum
t5-small-finetuned-xsum is a summarization model from hientptran. 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
- Dec 17, 2024
- Updated
- Dec 17, 2024
- SHA
- 9d4c4867
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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: 2.4727
- Rouge1: 28.3991
- Rouge2: 7.8164
- Rougel: 22.3432
- Rougelsum: 22.3542
- Gen Len: 18.8247
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.7009 | 1.0 | 12753 | 2.4727 | 28.3991 | 7.8164 | 22.3432 | 22.3542 | 18.8247 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3
- Task
- Summarization
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Dec 17, 2024
- Updated
- Dec 17, 2024