transformers pytorch tensorboard mt5 text2text-generation summarization generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
metrics:
- rouge
tags:
- summarization
- generated_from_trainer
model-index:
- name: mt5-small-finetuned-amazon-en-es
  results: []
---

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# 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: 3.0340
- Rouge1: 17.3678
- Rouge2: 8.5424
- Rougel: 17.0834
- Rougelsum: 17.0364

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 7.0197        | 1.0   | 1209 | 3.3037          | 13.6109 | 5.452  | 13.1481 | 13.0803   |
| 3.9145        | 2.0   | 2418 | 3.1418          | 15.5948 | 7.5705 | 14.8574 | 14.7619   |
| 3.5987        | 3.0   | 3627 | 3.0970          | 17.5045 | 8.7087 | 16.9058 | 16.7693   |
| 3.4274        | 4.0   | 4836 | 3.0672          | 16.7932 | 8.1293 | 16.1808 | 16.1062   |
| 3.3241        | 5.0   | 6045 | 3.0648          | 16.6776 | 8.2473 | 16.3764 | 16.3019   |
| 3.2468        | 6.0   | 7254 | 3.0444          | 17.2805 | 8.6933 | 17.0081 | 17.0303   |
| 3.2116        | 7.0   | 8463 | 3.0370          | 17.6236 | 8.7376 | 17.298  | 17.2475   |
| 3.1821        | 8.0   | 9672 | 3.0340          | 17.3678 | 8.5424 | 17.0834 | 17.0364   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
