AraBART-finetuned-xlsum

This model is a fine-tuned version of moussaKam/AraBART on an unknown dataset. It achieves the following results on the evaluation set:

• eval_loss: 2.0904
• eval_rouge1: 0.1176
• eval_rouge2: 0.0
• eval_rougeL: 0.1176
• eval_rougeLsum: 0.1176
• eval_runtime: 1.2306
• eval_samples_per_second: 13.815
• eval_steps_per_second: 2.438
• epoch: 3.7473
• step: 697

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: 8

Framework versions

• Transformers 4.42.4
• Pytorch 2.3.1+cu121
• Tokenizers 0.19.1