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sinMT5
Hamza-Ziyard/sinMT5
sinMT5 is a summarization model from Hamza-Ziyard. Use it when you need a shorter version of a longer text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Summarization
- Library
- transformers
- Model type
- mt5
- Access
- Public
- Created
- Apr 30, 2023
- Updated
- Apr 30, 2023
- SHA
- fa2b3310
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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. -->
mT5_multilingual_XLSum-sinhala-abstaractive-summarization_CNN-dailymail-V2
This model is a fine-tuned version of csebuetnlp/mT5_multilingual_XLSum on the CNN daily-mail sinhala dataset. It achieves the following results on the evaluation set:
- Loss: 2.4863
- Rouge1: 19.9769
- Rouge2: 8.04
- Rougel: 19.0307
- Rougelsum: 19.7651
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: 0.00056
- 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 1.8746 | 1.0 | 750 | 1.8262 | 18.9753 | 7.9271 | 18.1349 | 18.7152 |
| 1.4727 | 2.0 | 1500 | 1.8094 | 19.2219 | 7.9749 | 18.4314 | 18.9405 |
| 1.2331 | 3.0 | 2250 | 1.8432 | 20.436 | 7.8378 | 19.584 | 20.1613 |
| 1.0381 | 4.0 | 3000 | 1.8987 | 20.2251 | 7.9593 | 19.1556 | 19.9829 |
| 0.8737 | 5.0 | 3750 | 1.9471 | 20.3262 | 7.8935 | 19.407 | 20.0628 |
| 0.7363 | 6.0 | 4500 | 2.0611 | 20.1551 | 7.5046 | 19.2213 | 19.963 |
| 0.6214 | 7.0 | 5250 | 2.1838 | 19.9045 | 7.6232 | 18.743 | 19.5983 |
| 0.5277 | 8.0 | 6000 | 2.3190 | 20.8581 | 8.1054 | 19.8079 | 20.5414 |
| 0.4576 | 9.0 | 6750 | 2.4091 | 20.028 | 7.7635 | 19.0721 | 19.7053 |
| 0.4099 | 10.0 | 7500 | 2.4863 | 19.9769 | 8.04 | 19.0307 | 19.7651 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Summarization
- Library
- transformers
- Type
- mt5
- Created
- Apr 30, 2023
- Updated
- Apr 30, 2023