---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: opus-mt-en-mul-finetuned-lfn-to-en
  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. -->

# opus-mt-en-mul-finetuned-lfn-to-en

This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-mul](https://huggingface.co/Helsinki-NLP/opus-mt-en-mul) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6208
- Bleu: 62.9717
- Gen Len: 11.5165

## 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: 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| No log        | 1.0   | 290  | 0.9193          | 51.7454 | 11.5088 |
| 1.2009        | 2.0   | 580  | 0.7614          | 56.6817 | 11.4971 |
| 1.2009        | 3.0   | 870  | 0.6865          | 59.4575 | 11.4815 |
| 0.6524        | 4.0   | 1160 | 0.6545          | 60.9631 | 11.5088 |
| 0.6524        | 5.0   | 1450 | 0.6360          | 61.8171 | 11.5039 |
| 0.4903        | 6.0   | 1740 | 0.6337          | 61.9929 | 11.5049 |
| 0.4064        | 7.0   | 2030 | 0.6269          | 62.8025 | 11.5146 |
| 0.4064        | 8.0   | 2320 | 0.6234          | 62.5979 | 11.5292 |
| 0.3434        | 9.0   | 2610 | 0.6197          | 63.0131 | 11.5428 |
| 0.3434        | 10.0  | 2900 | 0.6208          | 62.9717 | 11.5165 |


### Framework versions

- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2