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sinMT5-tuned
Hamza-Ziyard/sinMT5-tuned
sinMT5-tuned 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
- May 7, 2023
- Updated
- May 8, 2023
- SHA
- 111f8bcc
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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. -->
sinMT5-tuned
This model is a fine-tuned version of google/mT5 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.8573
- Rouge1: 20.2531
- Rouge2: 8.1307
- Rougel: 19.3917
- Rougelsum: 20.0592
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: 0.00015652249866150822
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 1.8651 | 1.0 | 1500 | 1.8070 | 17.676 | 7.1418 | 16.8638 | 17.457 |
| 1.5527 | 2.0 | 3000 | 1.7804 | 21.1357 | 8.1386 | 20.122 | 20.8652 |
| 1.3755 | 3.0 | 4500 | 1.7769 | 21.4151 | 8.5692 | 20.3204 | 21.1152 |
| 1.2473 | 4.0 | 6000 | 1.7937 | 21.2434 | 8.2325 | 20.1332 | 21.0657 |
| 1.1548 | 5.0 | 7500 | 1.8035 | 20.4298 | 8.2314 | 19.5909 | 20.2116 |
| 1.0835 | 6.0 | 9000 | 1.8367 | 20.5427 | 8.2226 | 19.6134 | 20.2918 |
| 1.0387 | 7.0 | 10500 | 1.8573 | 20.2531 | 8.1307 | 19.3917 | 20.0592 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Tokenizers 0.13.3
- Task
- Summarization
- Library
- transformers
- Type
- mt5
- Created
- May 7, 2023
- Updated
- May 8, 2023