---
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
datasets:
- gazeta
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-amazon-en-es
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: gazeta
      type: gazeta
      config: default
      split: validation
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 9.9348
---

<!-- 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 gazeta dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2573
- Rouge1: 9.9348
- Rouge2: 1.4701
- Rougel: 9.7352
- Rougelsum: 9.7173

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 5.0727        | 1.0   | 763  | 2.4238          | 9.9038  | 2.2835 | 9.5715  | 9.6056    |
| 3.4561        | 2.0   | 1526 | 2.3779          | 10.5328 | 2.1668 | 10.297  | 10.2517   |
| 3.2731        | 3.0   | 2289 | 2.3248          | 11.0603 | 2.3552 | 10.9513 | 10.9458   |
| 3.1629        | 4.0   | 3052 | 2.2993          | 9.6206  | 1.553  | 9.4704  | 9.4079    |
| 3.0912        | 5.0   | 3815 | 2.2779          | 9.9379  | 1.5493 | 9.7858  | 9.7129    |
| 3.0449        | 6.0   | 4578 | 2.2698          | 10.1558 | 1.5231 | 9.947   | 9.8629    |
| 3.0184        | 7.0   | 5341 | 2.2683          | 9.7056  | 1.5373 | 9.4965  | 9.3964    |
| 2.9987        | 8.0   | 6104 | 2.2573          | 9.9348  | 1.4701 | 9.7352  | 9.7173    |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1