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---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- wiki_lingua
metrics:
- rouge
model-index:
- name: wiki_lingua-es-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: es
split: test
args: es
metrics:
- name: Rouge1
type: rouge
value: 22.4103
---
<!-- 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-es-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: 2.0242
- Rouge1: 22.4103
- Rouge2: 9.2461
- Rougel: 19.4105
- Rougelsum: 21.758
# Baseline LEAD-64
- Rouge1: 25.16
- Rouge2: 7.28
- Rougel: 16.23
- Rougelsum: 16.23
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 2.8922 | 1.0 | 9537 | 2.1216 | 21.4907 | 8.3405 | 18.2727 | 20.7713 |
| 2.4024 | 2.0 | 19074 | 2.0520 | 22.2765 | 9.1257 | 19.2788 | 21.608 |
| 2.3131 | 3.0 | 28611 | 2.0242 | 22.4103 | 9.2461 | 19.4105 | 21.758 |
### Framework versions
- Transformers 4.27.4
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2
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