transformers tensorboard safetensors mt5 text2text-generation summarization generated_from_trainer 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
library_name: transformers
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](https://huggingface.co/google/mt5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7039
- Rouge1: 18.8926
- Rouge2: 9.9716
- Rougel: 18.0984
- Rougelsum: 17.9782

## 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  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 4.018         | 1.0   | 611  | 2.8602          | 16.5049 | 7.8577  | 16.0553 | 15.8568   |
| 3.6801        | 2.0   | 1222 | 2.8070          | 14.4434 | 6.6539  | 14.122  | 13.817    |
| 3.4617        | 3.0   | 1833 | 2.7783          | 16.0718 | 7.8726  | 15.359  | 15.1215   |
| 3.3465        | 4.0   | 2444 | 2.7362          | 17.127  | 8.8774  | 16.4322 | 16.2438   |
| 3.2436        | 5.0   | 3055 | 2.7196          | 18.8253 | 9.9968  | 17.9656 | 17.9366   |
| 3.1844        | 6.0   | 3666 | 2.7137          | 18.8923 | 10.3424 | 18.215  | 18.1285   |
| 3.1241        | 7.0   | 4277 | 2.7102          | 18.3392 | 9.795   | 17.6282 | 17.4866   |
| 3.1074        | 8.0   | 4888 | 2.7039          | 18.8926 | 9.9716  | 18.0984 | 17.9782   |


### Framework versions

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