metadata
tags:
- mt5
- summarization
- Abstractive Summarization
- ar
- generated_from_trainer
datasets:
- xlsum
model-index:
- name: mT5_multilingual_XLSum-finetuned-fa-finetuned-ar
results: []
mT5_multilingual_XLSum-finetuned-fa-finetuned-ar
This model is a fine-tuned version of ahmeddbahaa/mT5_multilingual_XLSum-finetuned-fa on the xlsum dataset. It achieves the following results on the evaluation set:
- Loss: 3.6352
- Rouge-1: 28.69
- Rouge-2: 11.6
- Rouge-l: 24.29
- Gen Len: 41.37
- Bertscore: 73.37
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- num_epochs: 5
- label_smoothing_factor: 0.1
Training results
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1