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---
license: apache-2.0
base_model: google/mt5-base
tags:
- summarization
- generated_from_trainer
datasets:
- xlsum
metrics:
- rouge
model-index:
- name: mt5-base-xlsum
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: xlsum
type: xlsum
config: ukrainian
split: train
args: ukrainian
metrics:
- name: Rouge1
type: rouge
value: 2.98
---
<!-- 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-base-xlsum
This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the xlsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0396
- Rouge1: 2.98
- Rouge2: 0.1333
- Rougel: 3.0267
- Rougelsum: 2.9933
## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 5.3745 | 1.0 | 500 | 2.5041 | 1.0696 | 0.13 | 1.062 | 1.0629 |
| 3.413 | 2.0 | 1000 | 2.2178 | 1.8333 | 0.1333 | 1.84 | 1.8633 |
| 3.1052 | 3.0 | 1500 | 2.0844 | 3.14 | 0.2667 | 3.18 | 3.1733 |
| 2.9673 | 4.0 | 2000 | 2.0396 | 2.98 | 0.1333 | 3.0267 | 2.9933 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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