---
license: apache-2.0
base_model: Buseak/md_mt5_1911_v16_deneme
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: md_mt5_1911_v18_retrain
  results: []
---

<!-- 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. -->

# md_mt5_1911_v18_retrain

This model is a fine-tuned version of [Buseak/md_mt5_1911_v16_deneme](https://huggingface.co/Buseak/md_mt5_1911_v16_deneme) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1754
- Bleu: 0.7623
- Gen Len: 18.7866

## 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: 15

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu   | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|
| 0.6365        | 1.0   | 1250  | 0.3435          | 0.6788 | 18.7694 |
| 0.5732        | 2.0   | 2500  | 0.3064          | 0.7037 | 18.7644 |
| 0.5375        | 3.0   | 3750  | 0.2819          | 0.7114 | 18.7706 |
| 0.4912        | 4.0   | 5000  | 0.2549          | 0.7237 | 18.77   |
| 0.4648        | 5.0   | 6250  | 0.2394          | 0.7354 | 18.772  |
| 0.4321        | 6.0   | 7500  | 0.2245          | 0.7335 | 18.7762 |
| 0.4159        | 7.0   | 8750  | 0.2131          | 0.7446 | 18.778  |
| 0.4044        | 8.0   | 10000 | 0.2030          | 0.7478 | 18.7776 |
| 0.3889        | 9.0   | 11250 | 0.1963          | 0.7496 | 18.7852 |
| 0.3798        | 10.0  | 12500 | 0.1896          | 0.7524 | 18.7834 |
| 0.3733        | 11.0  | 13750 | 0.1836          | 0.757  | 18.7854 |
| 0.3623        | 12.0  | 15000 | 0.1803          | 0.7596 | 18.7852 |
| 0.3583        | 13.0  | 16250 | 0.1775          | 0.7618 | 18.7878 |
| 0.3643        | 14.0  | 17500 | 0.1758          | 0.7616 | 18.7828 |
| 0.3609        | 15.0  | 18750 | 0.1754          | 0.7623 | 18.7866 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0