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

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

## Model description

Elefen (or Lingua Franca Nova, abbreviated to "LFN") is a simple language designed for international communication.
Its vocabulary is based on Catalan, Spanish, French, Italian and Portuguese. The grammar is very reduced, similar to Romance creoles.

## 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

### Framework versions

- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
{"language": ["en", "lfn"], "license": "mit", "tags": ["generated_from_trainer"], "metrics": ["bleu"], "pipeline_tag": "translation", "base_model": "Helsinki-NLP/opus-mt-en-mul", "model-index": [{"name": "opus-mt-en-mul-finetuned-en-to-lfn", "results": []}]}
transformers pytorch tensorboard safetensors marian text2text-generation generated_from_trainer translation en lfn base_model:Helsinki-NLP/opus-mt-en-mul license:mit autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #tensorboard #safetensors #marian #text2text-generation #generated_from_trainer #translation #en #lfn #base_model-Helsinki-NLP/opus-mt-en-mul #license-mit #autotrain_compatible #endpoints_compatible #has_space #region-us 


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

This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-mul on the Tatoeba English-Elefen sentence pair dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6208
- Bleu: 62.9717
- Gen Len: 11.5165

## Model description

Elefen (or Lingua Franca Nova, abbreviated to "LFN") is a simple language designed for international communication.
Its vocabulary is based on Catalan, Spanish, French, Italian and Portuguese. The grammar is very reduced, similar to Romance creoles.

## 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

### Framework versions

- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
# opus-mt-en-mul-finetuned-en-to-lfn

This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-mul on the Tatoeba English-Elefen sentence pair dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6208
- Bleu: 62.9717
- Gen Len: 11.5165 ## Model description

Elefen (or Lingua Franca Nova, abbreviated to "LFN") is a simple language designed for international communication.
Its vocabulary is based on Catalan, Spanish, French, Italian and Portuguese. The grammar is very reduced, similar to Romance creoles. ## 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 ### Framework versions

- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #safetensors #marian #text2text-generation #generated_from_trainer #translation #en #lfn #base_model-Helsinki-NLP/opus-mt-en-mul #license-mit #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # opus-mt-en-mul-finetuned-en-to-lfn

This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-mul on the Tatoeba English-Elefen sentence pair dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6208
- Bleu: 62.9717
- Gen Len: 11.5165 ## Model description

Elefen (or Lingua Franca Nova, abbreviated to "LFN") is a simple language designed for international communication.
Its vocabulary is based on Catalan, Spanish, French, Italian and Portuguese. The grammar is very reduced, similar to Romance creoles. ## 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 ### Framework versions

- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #safetensors #marian #text2text-generation #generated_from_trainer #translation #en #lfn #base_model-Helsinki-NLP/opus-mt-en-mul #license-mit #autotrain_compatible #endpoints_compatible #has_space #region-us 
# opus-mt-en-mul-finetuned-en-to-lfn

This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-mul on the Tatoeba English-Elefen sentence pair dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6208
- Bleu: 62.9717
- Gen Len: 11.5165## Model description

Elefen (or Lingua Franca Nova, abbreviated to "LFN") is a simple language designed for international communication.
Its vocabulary is based on Catalan, Spanish, French, Italian and Portuguese. The grammar is very reduced, similar to Romance creoles.## 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### Framework versions

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