---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- mlsum
metrics:
- rouge
model-index:
- name: mt5-small-test-ged-mlsum_max_target_length_10
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: mlsum
      type: mlsum
      args: es
    metrics:
    - name: Rouge1
      type: rouge
      value: 74.8229
---

<!-- 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-small-test-ged-mlsum_max_target_length_10

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the mlsum dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3341
- Rouge1: 74.8229
- Rouge2: 68.1808
- Rougel: 74.8297
- Rougelsum: 74.8414

## 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: 8

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:------:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 0.5565        | 1.0   | 33296  | 0.3827          | 69.9041 | 62.821  | 69.8709 | 69.8924   |
| 0.2636        | 2.0   | 66592  | 0.3552          | 72.0701 | 65.4937 | 72.0787 | 72.091    |
| 0.2309        | 3.0   | 99888  | 0.3525          | 72.5071 | 65.8026 | 72.5132 | 72.512    |
| 0.2109        | 4.0   | 133184 | 0.3346          | 74.0842 | 67.4776 | 74.0887 | 74.0968   |
| 0.1972        | 5.0   | 166480 | 0.3398          | 74.6051 | 68.6024 | 74.6177 | 74.6365   |
| 0.1867        | 6.0   | 199776 | 0.3283          | 74.9022 | 68.2146 | 74.9023 | 74.926    |
| 0.1785        | 7.0   | 233072 | 0.3325          | 74.8631 | 68.2468 | 74.8843 | 74.9026   |
| 0.1725        | 8.0   | 266368 | 0.3341          | 74.8229 | 68.1808 | 74.8297 | 74.8414   |


### Framework versions

- Transformers 4.20.0
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1