---
library_name: transformers
license: apache-2.0
base_model: google/mt5-small
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 the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0229
- Bertscore Precision: 0.7189
- Bertscore Recall: 0.6939
- Bertscore F1: 0.7056

## 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: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Use OptimizerNames.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 | Bertscore Precision | Bertscore Recall | Bertscore F1 |
|:-------------:|:-----:|:-----:|:---------------:|:-------------------:|:----------------:|:------------:|
| 2.5119        | 1.0   | 1557  | 2.2031          | 0.711               | 0.6852           | 0.6972       |
| 2.5009        | 2.0   | 3114  | 2.1234          | 0.7154              | 0.6875           | 0.7005       |
| 2.4158        | 3.0   | 4671  | 2.0854          | 0.7165              | 0.6914           | 0.7032       |
| 2.3603        | 4.0   | 6228  | 2.0629          | 0.7166              | 0.6911           | 0.703        |
| 2.3206        | 5.0   | 7785  | 2.0451          | 0.7191              | 0.6934           | 0.7054       |
| 2.2938        | 6.0   | 9342  | 2.0328          | 0.718               | 0.6934           | 0.7049       |
| 2.2718        | 7.0   | 10899 | 2.0253          | 0.7191              | 0.6944           | 0.706        |
| 2.2622        | 8.0   | 12456 | 2.0229          | 0.7189              | 0.6939           | 0.7056       |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.7.1+cu118
- Datasets 2.14.6
- Tokenizers 0.21.1