---
license: apache-2.0
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: 3.2891
- Rouge1: 15.3337
- Rouge2: 6.5868
- Rougel: 14.7498
- Rougelsum: 14.7933

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 7.0622        | 1.0   | 1276  | 3.5617          | 13.2058 | 4.865  | 12.842  | 12.8295   |
| 4.0768        | 2.0   | 2552  | 3.4329          | 14.4762 | 6.5303 | 14.1011 | 14.0786   |
| 3.7736        | 3.0   | 3828  | 3.3393          | 15.2657 | 6.5763 | 14.6912 | 14.6868   |
| 3.5951        | 4.0   | 5104  | 3.3122          | 14.8748 | 6.2937 | 14.3369 | 14.4209   |
| 3.477         | 5.0   | 6380  | 3.2991          | 15.0897 | 6.475  | 14.7468 | 14.7971   |
| 3.4084        | 6.0   | 7656  | 3.3035          | 15.1618 | 6.331  | 14.5715 | 14.6335   |
| 3.3661        | 7.0   | 8932  | 3.2959          | 15.3575 | 6.7167 | 14.7582 | 14.8562   |
| 3.3457        | 8.0   | 10208 | 3.2891          | 15.3337 | 6.5868 | 14.7498 | 14.7933   |


### Framework versions

- Transformers 4.19.1
- Pytorch 1.7.0
- Datasets 2.2.1
- Tokenizers 0.12.1