---
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
datasets:
- xsum
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-amazon-en-es
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: xsum
      type: xsum
      config: default
      split: validation
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 0.0706
---

<!-- 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 xsum dataset.
It achieves the following results on the evaluation set:
- Loss: 5.4800
- Rouge1: 0.0706
- Rouge2: 0.0067
- Rougel: 0.058
- Rougelsum: 0.0654

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| No log        | 1.0   | 13   | 7.7221          | 0.0369 | 0.0    | 0.0369 | 0.0366    |
| No log        | 2.0   | 26   | 7.1952          | 0.0448 | 0.0    | 0.0452 | 0.0449    |
| No log        | 3.0   | 39   | 6.5146          | 0.0442 | 0.0    | 0.0443 | 0.044     |
| 12.6754       | 4.0   | 52   | 6.2530          | 0.0745 | 0.008  | 0.0636 | 0.0679    |
| 12.6754       | 5.0   | 65   | 6.0200          | 0.0745 | 0.0069 | 0.0642 | 0.0693    |
| 12.6754       | 6.0   | 78   | 5.7336          | 0.0706 | 0.0067 | 0.058  | 0.0654    |
| 12.6754       | 7.0   | 91   | 5.5400          | 0.0706 | 0.0067 | 0.058  | 0.0654    |
| 9.1744        | 8.0   | 104  | 5.4800          | 0.0706 | 0.0067 | 0.058  | 0.0654    |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu118
- Datasets 2.17.1
- Tokenizers 0.15.2