---
base_model: samzirbo/mT5.en-es.pretrained
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: baseline.europarl
  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. -->

# baseline.europarl

This model is a fine-tuned version of [samzirbo/mT5.en-es.pretrained](https://huggingface.co/samzirbo/mT5.en-es.pretrained) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5556
- Bleu: 28.4134
- Meteor: 0.548
- Chrf++: 50.7588

## 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: 0.0005
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- training_steps: 50000

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Meteor | Chrf++  |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|
| 3.7368        | 0.06  | 2500  | 3.7330          | 16.6348 | 0.4263 | 38.9851 |
| 1.9501        | 0.11  | 5000  | 3.6988          | 20.5694 | 0.4632 | 42.6268 |
| 1.7374        | 0.17  | 7500  | 3.6554          | 21.8374 | 0.4825 | 44.4332 |
| 1.6252        | 0.23  | 10000 | 3.6674          | 23.1212 | 0.4954 | 45.8093 |
| 1.5421        | 0.28  | 12500 | 3.6407          | 24.144  | 0.5063 | 47.0076 |
| 1.4867        | 0.34  | 15000 | 3.6991          | 23.9884 | 0.5055 | 46.9973 |
| 1.4413        | 0.39  | 17500 | 3.6669          | 25.0356 | 0.5135 | 47.6982 |
| 1.4017        | 0.45  | 20000 | 3.5988          | 25.4766 | 0.5201 | 48.3754 |
| 1.3769        | 0.51  | 22500 | 3.6120          | 26.17   | 0.5295 | 49.037  |
| 1.3476        | 0.56  | 25000 | 3.6225          | 26.8343 | 0.5341 | 49.5501 |
| 1.3252        | 0.62  | 27500 | 3.5913          | 26.7117 | 0.5321 | 49.3981 |
| 1.307         | 0.68  | 30000 | 3.6205          | 27.3269 | 0.5385 | 49.9517 |
| 1.2926        | 0.73  | 32500 | 3.5624          | 27.7597 | 0.5446 | 50.3568 |
| 1.2823        | 0.79  | 35000 | 3.5449          | 27.8457 | 0.5458 | 50.5179 |
| 1.2728        | 0.85  | 37500 | 3.5383          | 27.9605 | 0.5444 | 50.3421 |
| 1.2663        | 0.9   | 40000 | 3.5556          | 28.1962 | 0.5465 | 50.5512 |
| 1.2628        | 0.96  | 42500 | 3.5498          | 28.3077 | 0.5477 | 50.7074 |
| 1.2514        | 1.01  | 45000 | 3.5519          | 28.3543 | 0.548  | 50.7669 |
| 1.239         | 1.07  | 47500 | 3.5555          | 28.2177 | 0.5473 | 50.6922 |
| 1.2357        | 1.13  | 50000 | 3.5556          | 28.4134 | 0.548  | 50.7588 |


### Framework versions

- Transformers 4.38.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.15.2