---
base_model: kravchenko/uk-mt5-base
tags:
- summarization
- generated_from_trainer
datasets:
- xlsum
metrics:
- rouge
model-index:
- name: uk-mt5-base-xlsum
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: xlsum
      type: xlsum
      config: ukrainian
      split: validation
      args: ukrainian
    metrics:
    - name: Rouge1
      type: rouge
      value: 3.8556
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# uk-mt5-base-xlsum

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: 2.3660
- Rouge1: 3.8556
- Rouge2: 1.5556
- Rougel: 3.7833
- Rougelsum: 3.6889

## 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: 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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 5.31          | 1.0   | 375  | 2.5055          | 2.3333 | 0.8    | 2.3143 | 2.3238    |
| 3.254         | 2.0   | 750  | 2.4034          | 3.5444 | 1.1111 | 3.5333 | 3.4833    |
| 2.9813        | 3.0   | 1125 | 2.3844          | 3.7278 | 1.4444 | 3.6889 | 3.6333    |
| 2.8117        | 4.0   | 1500 | 2.3785          | 3.3222 | 1.1111 | 3.2556 | 3.2167    |
| 2.681         | 5.0   | 1875 | 2.3671          | 4.1667 | 1.5556 | 4.0667 | 4.0444    |
| 2.5825        | 6.0   | 2250 | 2.3705          | 3.6889 | 1.5556 | 3.6    | 3.5333    |
| 2.5151        | 7.0   | 2625 | 2.3654          | 3.6889 | 1.5556 | 3.6    | 3.5333    |
| 2.4798        | 8.0   | 3000 | 2.3660          | 3.8556 | 1.5556 | 3.7833 | 3.6889    |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1