mt5-base-turkish-summarization – AI Model by mukayese | AlphaNeural AI

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mukayese/
mt5-base-turkish-summarization

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text2text-generation

generated_from_trainer

google/mt5-base

endpoints_compatible

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Mukayese: Turkish NLP Strikes Back

Summarization: mukayese/mbart-large-turkish-sum

This model is a fine-tuned version of google/mt5-base on the mlsum/tu dataset.

It achieves the following results on the evaluation set:

Rouge1: 47.4222
Rouge2: 34.8624
Rougel: 42.2487
Rougelsum: 43.9494

Check this paper for more details on the model and the dataset.

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.0005
train_batch_size: 2
eval_batch_size: 4
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 4
total_train_batch_size: 64
total_eval_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10.0
label_smoothing_factor: 0.1

Framework versions

Transformers 4.11.3
Pytorch 1.8.2+cu111
Datasets 1.14.0
Tokenizers 0.10.3

Citation

@misc{safaya-etal-2022-mukayese,
    title={Mukayese: Turkish NLP Strikes Back},
    author={Ali Safaya and Emirhan Kurtuluş and Arda Göktoğan and Deniz Yuret},
    year={2022},
    eprint={2203.01215},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}