transformers pytorch mt5 text2text-generation summarization generated_from_trainer base_model:google/mt5-small base_model:finetune:google/mt5-small license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
base_model: google/mt5-small
license: apache-2.0
metrics:
- rouge
tags:
- summarization
- generated_from_trainer
model-index:
- name: mt5-small-finetuned-tr-news
  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. -->

# mt5-small-finetuned-tr-news

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3748
- Rouge1: 25.2124
- Rouge2: 13.3894
- Rougel: 22.4063
- Rougelsum: 22.9668

## 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: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 5.5375        | 1.0   | 875  | 2.5866          | 22.5826 | 11.7162 | 19.8221 | 20.1884   |
| 3.3129        | 2.0   | 1750 | 2.5237          | 23.8445 | 12.7539 | 21.3485 | 21.7204   |
| 3.0876        | 3.0   | 2625 | 2.4728          | 24.1288 | 12.5373 | 21.4068 | 21.8723   |
| 2.9685        | 4.0   | 3500 | 2.4348          | 25.3884 | 13.3569 | 22.5336 | 23.0989   |
| 2.8886        | 5.0   | 4375 | 2.4043          | 25.5798 | 13.7628 | 22.7085 | 23.2025   |
| 2.836         | 6.0   | 5250 | 2.3813          | 24.93   | 13.2058 | 22.2455 | 22.6959   |
| 2.8069        | 7.0   | 6125 | 2.3800          | 24.8104 | 12.9556 | 22.1114 | 22.6108   |
| 2.7813        | 8.0   | 7000 | 2.3748          | 25.2124 | 13.3894 | 22.4063 | 22.9668   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1
