Mt5 Base Finetuned English Finetuned English Arabic

🚀 mt5-base-finetuned-english-finetuned-english-arabic

This model is a fine - tuned version of eslamxm/mt5-base-finetuned-english on the xlsum dataset, aiming at summarization tasks in both English and Arabic.

🚀 Quick Start

This model is a fine - tuned version of eslamxm/mt5-base-finetuned-english on the xlsum dataset. It achieves the following results on the evaluation set:

• Loss: 3.4788
• Rouge - 1: 22.55
• Rouge - 2: 9.84
• Rouge - l: 20.5
• Gen Len: 19.0
• Bertscore: 71.39

📚 Documentation

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: 0.0005
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon = 1e - 08
• lr_scheduler_type: linear
• num_epochs: 5
• label_smoothing_factor: 0.1

Training results

Framework versions

• Transformers 4.19.0
• Pytorch 1.11.0+cu113
• Datasets 2.2.1
• Tokenizers 0.12.1

📄 License

This model is licensed under the Apache - 2.0 license.