---
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
datasets:
- wcep-10
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-amazon-en-es
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: wcep-10
      type: wcep-10
      config: roberta
      split: validation
      args: roberta
    metrics:
    - name: Rouge1
      type: rouge
      value: 22.6862
---

<!-- 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 wcep-10 dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1575
- Rouge1: 22.6862
- Rouge2: 7.7268
- Rougel: 19.1961
- Rougelsum: 19.3808

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 6.5905        | 1.0   | 1020 | 3.4711          | 21.2268 | 7.4345 | 18.5023 | 18.6264   |
| 4.1604        | 2.0   | 2040 | 3.3228          | 21.6354 | 7.3939 | 18.4926 | 18.6047   |
| 3.914         | 3.0   | 3060 | 3.2606          | 21.9787 | 7.5818 | 18.6971 | 18.8603   |
| 3.7698        | 4.0   | 4080 | 3.2058          | 21.8859 | 7.5625 | 18.6413 | 18.8169   |
| 3.679         | 5.0   | 5100 | 3.1824          | 22.6515 | 7.7467 | 19.1196 | 19.3121   |
| 3.6131        | 6.0   | 6120 | 3.1678          | 22.0223 | 7.6153 | 18.7956 | 18.9968   |
| 3.5722        | 7.0   | 7140 | 3.1631          | 22.679  | 7.7952 | 19.1784 | 19.384    |
| 3.5432        | 8.0   | 8160 | 3.1575          | 22.6862 | 7.7268 | 19.1961 | 19.3808   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1