mT5-Xl Turkish Summarization
This model is a fine-tuned version of google/mt5-xl on the musabg/wikipedia-tr-summarization dataset.
This can be used with HF summarization pipeline.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0
Eval results
It achieves the following results on the evaluation set:
- Loss: 0.5676
- Rouge1: 56.4468
- Rouge2: 41.3258
- Rougel: 48.1909
- Rougelsum: 48.4284
- Gen Len: 75.9265
Training results
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 1.13.1
- Datasets 2.12.0
- Tokenizers 0.13.3
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Dataset used to train musabg/mt5-xl-tr-summarization
Evaluation results
- Rouge1 on musabg/wikipedia-tr-summarizationvalidation set self-reported56.447