---
license: apache-2.0
base_model: facebook/bart-base
tags:
- generated_from_trainer
datasets:
- opus_books
metrics:
- bleu
model-index:
- name: en-to-es-trans-with-bart
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: opus_books
      type: opus_books
      config: en-es
      split: train
      args: en-es
    metrics:
    - name: Bleu
      type: bleu
      value: 2.1888
---

<!-- 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. -->

# en-to-es-trans-with-bart

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co./facebook/bart-base) on the opus_books dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0355
- Bleu: 2.1888
- Gen Len: 18.6278

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| 2.4648        | 1.0   | 4674 | 2.1509          | 1.937  | 18.6399 |
| 2.2417        | 2.0   | 9348 | 2.0355          | 2.1888 | 18.6278 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0