--- tags: - generated_from_trainer metrics: - rouge model-index: - name: mbert2mbert-arabic-text-summarization-finetuned-xsum_arabic_abstractive_final_finaln results: [] --- # mbert2mbert-arabic-text-summarization-finetuned-xsum_arabic_abstractive_final_finaln This model is a fine-tuned version of [malmarjeh/mbert2mbert-arabic-text-summarization](https://huggingface.co/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