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mt5-small-finetuned-amazon-en-es
libalabala/mt5-small-finetuned-amazon-en-es
mt5-small-finetuned-amazon-en-es is a summarization model from libalabala. 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
- Mar 17, 2022
- Updated
- Mar 24, 2022
- SHA
- 942027a1
Try a prompt
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-finetuned-amazon-en-es
This model is a fine-tuned version of google/mt5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.1997
- Rouge1: 16.7312
- Rouge2: 8.6607
- Rougel: 16.1846
- Rougelsum: 16.2411
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: 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 7.0772 | 1.0 | 1209 | 3.3307 | 12.4644 | 4.0353 | 12.0167 | 12.0722 |
| 4.0223 | 2.0 | 2418 | 3.2257 | 15.338 | 7.0168 | 14.7769 | 14.8391 |
| 3.8018 | 3.0 | 3627 | 3.1997 | 16.7312 | 8.6607 | 16.1846 | 16.2411 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6
- Task
- Summarization
- Library
- transformers
- Type
- mt5
- License
- apache-2.0
- Created
- Mar 17, 2022
- Updated
- Mar 24, 2022