README.md

---
license: mit
base_model: Helsinki-NLP/opus-mt-en-es
tags:
- translation
- UPV
- MIARFID
- EuroParl
model-index:
  - name: dap305/Helsinki-finetuned-EuroParl-en-to-es
    results:
      - task:
          type: translation
          name: Translation En-to-ES
        dataset:
          type: translation
          name: EuroParl.V7.Subset
        metrics:
          - type: bleu
            value: 37.083
language:
- en
- es
metrics:
- bleu
library_name: transformers
pipeline_tag: translation
datasets:
- dap305/processed_europarlv7_subset50k
---

# dap305/Helsinki-finetuned-EuroParl-en-to-es

This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-es](https://huggingface.co/Helsinki-NLP/opus-mt-en-es) on a subset of the EuroParl dataset.
It achieves the following results on the validation set:
- Train Loss: 0.9863
- Validation Loss: 1.1352
- BLUE: 37.083

## Intended uses & limitations

This model has been created for learning purposes at the MIARFID Automatic Translation course. 

## Training and evaluation data

This model was fine-tuned with a subset of the Europarl-v7-es-en, consisting of 50.000 sentences in English and Spanish.

Philipp Koehn. 2005. Europarl: A Parallel Corpus for Statistical Machine Translation. In Proceedings of Machine Translation Summit X: Papers, pages 79–86, Phuket, Thailand.

### Training hyperparameters

The following hyperparameters were used during training:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 4344, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: mixed_float16

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 1.2441     | 1.1487          | 0     |
| 1.0785     | 1.1351          | 1     |
| 0.9863     | 1.1352          | 2     |


### Framework versions

- Transformers 4.37.0
- TensorFlow 2.13.0
- Datasets 2.16.1
- Tokenizers 0.15.1