---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- null
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-amazon-en-es
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    metrics:
    - name: Rouge1
      type: rouge
      value: 12.4927
---

<!-- 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-finetuned-amazon-en-es

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9894
- Rouge1: 12.4927
- Rouge2: 4.847
- Rougel: 12.4387
- Rougelsum: 12.4383
- Gen Len: 6.1675

## 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: 4e-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 | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 6.5619        | 1.0   | 2202  | 3.2749          | 9.2423  | 3.2813 | 9.2013  | 9.1698    | 5.0354  |
| 3.8525        | 2.0   | 4404  | 3.1296          | 11.1883 | 4.047  | 11.1545 | 11.1885   | 6.4033  |
| 3.5419        | 3.0   | 6606  | 3.0478          | 11.4905 | 4.4465 | 11.3538 | 11.3805   | 6.6462  |
| 3.4045        | 4.0   | 8808  | 3.0174          | 11.5798 | 4.4426 | 11.5372 | 11.571    | 6.6816  |
| 3.3091        | 5.0   | 11010 | 3.0080          | 12.0207 | 4.5622 | 11.9232 | 11.9476   | 6.4976  |
| 3.2457        | 6.0   | 13212 | 2.9981          | 12.2459 | 4.6924 | 12.2306 | 12.2375   | 6.1533  |
| 3.2179        | 7.0   | 15414 | 2.9943          | 12.3927 | 4.6072 | 12.2888 | 12.2848   | 6.3561  |
| 3.1898        | 8.0   | 17616 | 2.9894          | 12.4927 | 4.847  | 12.4387 | 12.4383   | 6.1675  |


### Framework versions

- Transformers 4.10.3
- Pytorch 1.9.1+cu111
- Datasets 1.12.1
- Tokenizers 0.10.3