---
library_name: transformers
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
datasets:
- mlsum
metrics:
- rouge
model-index:
- name: flan-t5-base-turkish-summarisation
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: mlsum
      type: mlsum
      config: tu
      split: validation
      args: tu
    metrics:
    - name: Rouge1
      type: rouge
      value: 17.7215
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# flan-t5-base-turkish-summarisation

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the mlsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2759
- Rouge1: 17.7215
- Rouge2: 11.6449
- Rougel: 17.1215
- Rougelsum: 17.0317
- Gen Len: 20.0

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- training_steps: 1000

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.5856        | 0.0802 | 200  | 1.3164          | 18.0769 | 11.7482 | 17.3132 | 17.32     | 20.0    |
| 1.4888        | 0.1604 | 400  | 1.2901          | 17.6893 | 11.6682 | 16.9148 | 16.8964   | 20.0    |
| 1.4787        | 0.2407 | 600  | 1.2827          | 17.5252 | 11.5143 | 16.8586 | 16.8281   | 20.0    |
| 1.488         | 0.3209 | 800  | 1.2637          | 17.8913 | 11.7712 | 17.1369 | 17.0949   | 20.0    |
| 1.4105        | 0.4011 | 1000 | 1.2759          | 17.7215 | 11.6449 | 17.1215 | 17.0317   | 20.0    |


### Framework versions

- Transformers 4.48.0
- Pytorch 2.2.2
- Datasets 3.2.0
- Tokenizers 0.21.0