---
library_name: transformers
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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2659
- Rouge1: 13.7437
- Rouge2: 5.9153
- Rougel: 13.4146

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|
| 9.4301        | 1.0   | 625  | 3.5851          | 8.6109  | 2.4991 | 8.3173  |
| 4.6907        | 2.0   | 1250 | 3.4105          | 11.1544 | 4.3475 | 10.7786 |
| 4.1916        | 3.0   | 1875 | 3.3443          | 10.8192 | 3.848  | 10.44   |
| 3.971         | 4.0   | 2500 | 3.3001          | 12.7096 | 5.0292 | 12.3085 |
| 3.8402        | 5.0   | 3125 | 3.2788          | 12.1184 | 4.5893 | 11.7314 |
| 3.7106        | 6.0   | 3750 | 3.2795          | 13.748  | 5.907  | 13.5413 |
| 3.6523        | 7.0   | 4375 | 3.2702          | 13.6669 | 5.8956 | 13.3843 |
| 3.6315        | 8.0   | 5000 | 3.2659          | 13.7437 | 5.9153 | 13.4146 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3