---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- musabg/wikipedia-tr-summarization
metrics:
- rouge
model-index:
- name: mt5-xl-tr-summarization
  results:
  - task:
      name: Summarization
      type: summarization
    dataset:
      name: musabg/wikipedia-tr-summarization
      type: musabg/wikipedia-tr-summarization
      split: validation
    metrics:
    - name: Rouge1
      type: rouge
      value: 56.4468
language:
- tr
---

# mT5-Xl Turkish Summarization

This model is a fine-tuned version of [google/mt5-xl](https://huggingface.co/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