---
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-amazon-en-es
  results: []
---

<!-- 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: nan
- Rouge1: 0.0
- Rouge2: 0.0
- Rougel: 0.0
- Rougelsum: 0.0

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 0.0           | 1.0   | 1209 | nan             | 0.0    | 0.0    | 0.0    | 0.0       |
| 0.0           | 2.0   | 2418 | nan             | 0.0    | 0.0    | 0.0    | 0.0       |
| 0.0           | 3.0   | 3627 | nan             | 0.0    | 0.0    | 0.0    | 0.0       |
| 0.0           | 4.0   | 4836 | nan             | 0.0    | 0.0    | 0.0    | 0.0       |
| 0.0           | 5.0   | 6045 | nan             | 0.0    | 0.0    | 0.0    | 0.0       |
| 0.0           | 6.0   | 7254 | nan             | 0.0    | 0.0    | 0.0    | 0.0       |
| 0.0           | 7.0   | 8463 | nan             | 0.0    | 0.0    | 0.0    | 0.0       |
| 0.0           | 8.0   | 9672 | nan             | 0.0    | 0.0    | 0.0    | 0.0       |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3