mbert2mbert-arabic-text-summarization-finetuned-xsum_arabic_abstractive_final_finaln

This model is a fine-tuned version of malmarjeh/mbert2mbert-arabic-text-summarization on the None dataset. It achieves the following results on the evaluation set:

• Loss: 2.2826
• Rouge1: 0.0119
• Rouge2: 0.0
• Rougel: 0.0119
• Rougelsum: 0.0119
• Gen Len: 41.8856

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: 2e-05
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.5104	1.0	7915	2.3684	0.0	0.0	0.0	0.0	41.8314
2.2222	2.0	15830	2.2826	0.0119	0.0	0.0119	0.0119	41.8856

Framework versions

• Transformers 4.20.1
• Pytorch 1.11.0
• Datasets 2.1.0
• Tokenizers 0.12.1