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mt5-small-cnn-dm-kaggle-en
pendulum27/mt5-small-cnn-dm-kaggle-en
mt5-small-cnn-dm-kaggle-en is a summarization model from pendulum27. 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
- mt5
- Access
- Public
- Created
- May 27, 2023
- Updated
- Nov 7, 2023
- SHA
- 19ea6504
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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. -->
mt5-small-cnn-dm-kaggle-en
This model is a fine-tuned version of google/mt5-small on the cnn_dailymail dataset. It achieves the following results on the evaluation set:
- Loss: 3.2499
- Rouge1: 25.24
- Rouge2: 11.4243
- Rougel: 22.1837
- Rougelsum: 22.2212
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: 5.6e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 3.7959 | 1.0 | 2668 | 3.3796 | 24.6486 | 10.95 | 21.6027 | 21.6371 |
| 3.6116 | 2.0 | 5336 | 3.2863 | 25.0485 | 11.2204 | 21.9543 | 21.9949 |
| 3.5264 | 3.0 | 8004 | 3.2426 | 25.1151 | 11.2913 | 22.0778 | 22.1108 |
| 3.4845 | 4.0 | 10672 | 3.2499 | 25.24 | 11.4243 | 22.1837 | 22.2212 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
- Task
- Summarization
- Library
- transformers
- Type
- mt5
- License
- apache-2.0
- Languages
- en
- Created
- May 27, 2023
- Updated
- Nov 7, 2023