transformers pytorch mt5 text2text-generation summarization generated_from_trainer en es dataset:amazon_reviews_multi base_model:google/mt5-small base_model:finetune:google/mt5-small license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
base_model: google/mt5-small
datasets:
- amazon_reviews_multi
language:
- en
- es
license: apache-2.0
metrics:
- rouge
tags:
- summarization
- generated_from_trainer
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 on the amazon_reviews_multi dataset (https://huggingface.co/datasets/amazon_reviews_multi), 
with a filter applied to reviews about books.

The filter_books function is used to filter examples in the data and returns only those that belong to the "book" or "digital ebook purchase" category.


It achieves the following results on the evaluation set:
- Loss: 3.0270
- Rouge1: 16.8614
- Rouge2: 8.3352
- Rougel: 16.5595
- Rougelsum: 16.5755

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 7.376         | 1.0   | 1209 | 3.3114          | 13.6834 | 5.4759 | 13.2778 | 13.3315   |
| 3.9197        | 2.0   | 2418 | 3.1662          | 15.4107 | 7.396  | 15.0443 | 15.0493   |
| 3.5954        | 3.0   | 3627 | 3.0844          | 15.4126 | 7.2537 | 15.0816 | 15.1281   |
| 3.4243        | 4.0   | 4836 | 3.0384          | 15.9869 | 7.7568 | 15.7054 | 15.6149   |
| 3.3145        | 5.0   | 6045 | 3.0512          | 17.3119 | 8.412  | 16.8461 | 16.7631   |
| 3.2597        | 6.0   | 7254 | 3.0237          | 16.7165 | 7.9706 | 16.4276 | 16.3935   |
| 3.2094        | 7.0   | 8463 | 3.0308          | 17.4737 | 8.7048 | 17.0836 | 17.0624   |
| 3.1886        | 8.0   | 9672 | 3.0270          | 16.8614 | 8.3352 | 16.5595 | 16.5755   |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cpu
- Datasets 2.14.5
- Tokenizers 0.13.3