Mt5 Base Turkish Summarization

🚀 mt5-base-turkish-sum

A fine - tuned model for Turkish text summarization based on google/mt5 - base, achieving good results on the mlsum/tu dataset.

🚀 Quick Start

This model is a fine - tuned version of [google/mt5 - base](https://huggingface.co/google/mt5 - base) on the mlsum/tu dataset. It can be used for Turkish text summarization tasks.

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.

📚 Documentation

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}
}

📄 License

This model is released under the Apache 2.0 license.

📦 Model Information