---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: bart-base-en-to-de
  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. -->

# bart-base-en-to-de

This model is a fine-tuned version of [ahazeemi/bart-base-finetuned-en-to-de](https://huggingface.co/ahazeemi/bart-base-finetuned-en-to-de) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9665
- Bleu: 4.7851
- Gen Len: 19.453

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Bleu   | Gen Len |
|:-------------:|:-----:|:------:|:---------------:|:------:|:-------:|
| 1.319         | 0.04  | 5000   | 1.1247          | 4.4467 | 19.447  |
| 1.295         | 0.07  | 10000  | 1.1012          | 4.4235 | 19.458  |
| 1.2901        | 0.11  | 15000  | 1.0923          | 4.4386 | 19.4423 |
| 1.2678        | 0.14  | 20000  | 1.0803          | 4.5259 | 19.4557 |
| 1.267         | 0.18  | 25000  | 1.0724          | 4.5534 | 19.4653 |
| 1.2444        | 0.21  | 30000  | 1.0591          | 4.4944 | 19.4623 |
| 1.2365        | 0.25  | 35000  | 1.0509          | 4.5736 | 19.446  |
| 1.2137        | 0.28  | 40000  | 1.0400          | 4.5346 | 19.4553 |
| 1.214         | 0.32  | 45000  | 1.0340          | 4.5733 | 19.4543 |
| 1.218         | 0.35  | 50000  | 1.0283          | 4.6076 | 19.4693 |
| 1.2118        | 0.39  | 55000  | 1.0225          | 4.6192 | 19.454  |
| 1.1948        | 0.43  | 60000  | 1.0152          | 4.6082 | 19.4553 |
| 1.1932        | 0.46  | 65000  | 1.0128          | 4.665  | 19.449  |
| 1.1889        | 0.5   | 70000  | 1.0028          | 4.6929 | 19.4493 |
| 1.2154        | 0.53  | 75000  | 1.0004          | 4.7151 | 19.4477 |
| 1.194         | 0.57  | 80000  | 0.9950          | 4.6655 | 19.467  |
| 1.1847        | 0.6   | 85000  | 0.9966          | 4.708  | 19.451  |
| 1.1848        | 0.64  | 90000  | 0.9897          | 4.7794 | 19.458  |
| 1.1762        | 0.67  | 95000  | 0.9866          | 4.7204 | 19.4523 |
| 1.1818        | 0.71  | 100000 | 0.9803          | 4.7137 | 19.458  |
| 1.1613        | 0.75  | 105000 | 0.9788          | 4.7652 | 19.4573 |
| 1.1738        | 0.78  | 110000 | 0.9775          | 4.8088 | 19.453  |
| 1.1569        | 0.82  | 115000 | 0.9752          | 4.7522 | 19.4577 |
| 1.1631        | 0.85  | 120000 | 0.9713          | 4.7301 | 19.4513 |
| 1.1517        | 0.89  | 125000 | 0.9690          | 4.7935 | 19.456  |
| 1.1577        | 0.92  | 130000 | 0.9686          | 4.791  | 19.4543 |
| 1.1607        | 0.96  | 135000 | 0.9676          | 4.7529 | 19.4533 |
| 1.153         | 0.99  | 140000 | 0.9665          | 4.7851 | 19.453  |


### Framework versions

- Transformers 4.22.2
- Pytorch 1.12.0+cu116
- Datasets 2.5.1
- Tokenizers 0.12.1