mt5-small-finetuned-xlsum-en-es
This model is a fine-tuned version of google/mt5-small on the csebuetnlp/xlsum dataset.
Reduced versions of the English/Spanish subsets were used, focusing on shorter targets.
It achieves the following results on the evaluation set:
- Loss: 2.9483
- Rouge1: 19.42
- Rouge2: 4.44
- Rougel: 16.7
- Rougelsum: 16.7
- Mean Len: 16.3231
Model description
More information needed
Intended uses & limitations
Model may produce false information when summarizing.
This is very much an initial draft, and is not expected for use in production, use at your own risk.
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Lead-3 Baseline:
- Rouge1: 12.22
- Rouge2: 2.01
- RougeL: 9.02
- RougeLsum: 10.33
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Mean Len |
---|---|---|---|---|---|---|---|---|
6.7763 | 1.0 | 1237 | 3.1120 | 13.57 | 2.76 | 11.59 | 11.59 | 12.6116 |
4.1022 | 2.0 | 2474 | 2.9718 | 19.35 | 4.32 | 16.63 | 16.64 | 16.3084 |
3.9219 | 3.0 | 3711 | 2.9483 | 19.42 | 4.44 | 16.7 | 16.7 | 16.3231 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
Citation
BibTeX:
@inproceedings{hasan-etal-2021-xl,
title = "{XL}-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages",
author = "Hasan, Tahmid and
Bhattacharjee, Abhik and
Islam, Md. Saiful and
Mubasshir, Kazi and
Li, Yuan-Fang and
Kang, Yong-Bin and
Rahman, M. Sohel and
Shahriyar, Rifat",
booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.findings-acl.413",
pages = "4693--4703",
}
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