transformers pytorch mt5 text2text-generation summarization generated_from_trainer dataset:xlsum base_model:kravchenko/uk-mt5-base base_model:finetune:kravchenko/uk-mt5-base model-index autotrain_compatible endpoints_compatible region:us
---
base_model: kravchenko/uk-mt5-base
datasets:
- xlsum
metrics:
- rouge
tags:
- summarization
- generated_from_trainer
model-index:
- name: uk-mt5-base-xlsum-v3
  results:
  - task:
      type: text2text-generation
      name: Sequence-to-sequence Language Modeling
    dataset:
      name: xlsum
      type: xlsum
      config: ukrainian
      split: validation
      args: ukrainian
    metrics:
    - type: rouge
      value: 4.0823
      name: Rouge1
---

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# uk-mt5-base-xlsum-v3

This model is a fine-tuned version of [kravchenko/uk-mt5-base](https://huggingface.co/kravchenko/uk-mt5-base) on the xlsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7752
- Rouge1: 4.0823
- Rouge2: 0.8039
- Rougel: 4.0033
- Rougelsum: 4.0125

## 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: 9

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.8372        | 1.0   | 3413  | 1.9145          | 2.8041 | 0.6205 | 2.8045 | 2.8124    |
| 2.3863        | 2.0   | 6826  | 1.8516          | 3.3759 | 0.5435 | 3.3257 | 3.3414    |
| 2.2434        | 3.0   | 10239 | 1.8298          | 3.6535 | 0.6412 | 3.6527 | 3.6437    |
| 2.2593        | 4.0   | 13652 | 1.8232          | 3.7021 | 0.6361 | 3.6648 | 3.685     |
| 2.2084        | 5.0   | 17065 | 1.8081          | 3.8312 | 0.6814 | 3.7756 | 3.7865    |
| 2.1702        | 6.0   | 20478 | 1.8012          | 3.7021 | 0.6141 | 3.6663 | 3.6728    |
| 2.1449        | 7.0   | 23891 | 1.7901          | 3.88   | 0.6412 | 3.8275 | 3.8328    |
| 2.1032        | 8.0   | 27304 | 1.7788          | 3.8141 | 0.7171 | 3.7729 | 3.761     |
| 2.0779        | 9.0   | 30717 | 1.7752          | 4.0823 | 0.8039 | 4.0033 | 4.0125    |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
