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---
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
should probably proofread and complete it, then remove this comment. -->
# 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
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