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---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- wiki_lingua
metrics:
- rouge
model-index:
- name: wiki_lingua-de-8-3-5.6e-05-mt5-small-finetuned
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: wiki_lingua
type: wiki_lingua
config: de
split: test
args: de
metrics:
- name: Rouge1
type: rouge
value: 15.2299
language:
- de
---
<!-- 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. -->
# wiki_lingua-de-8-3-5.6e-05-mt5-small-finetuned
This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the wiki_lingua dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4218
- Rouge1: 15.2299
- Rouge2: 4.4912
- Rougel: 13.4991
- Rougelsum: 14.9193
# Baseline LEAD64
- Rouge1: 18.76
- Rouge2: 4.22
- Rougel: 12.14
- Rougelsum: 12.14
## 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: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 3.5656 | 1.0 | 4939 | 2.5421 | 14.4738 | 4.064 | 12.7061 | 14.1813 |
| 2.9444 | 2.0 | 9878 | 2.4492 | 14.8349 | 4.3457 | 13.16 | 14.5623 |
| 2.8378 | 3.0 | 14817 | 2.4218 | 15.2299 | 4.4912 | 13.4991 | 14.9193 |
### Framework versions
- Transformers 4.27.4
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2 |