mbert_5_30_000

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: 0.2958
• Rouge1: 10.0933
• Rouge2: 4.1011
• Rougel: 10.1123
• Rougelsum: 10.142
• Gen Len: 41.2852

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: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
0.3149	1.0	1676	0.2958	10.0933	4.1011	10.1123	10.142	41.2852

Framework versions

• Transformers 4.30.2
• Pytorch 2.0.1+cu118
• Datasets 2.13.0
• Tokenizers 0.13.3