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# model_zu-en_updated

This model is a fine-tuned version of [Helsinki-NLP/opus-mt-mul-en](https://huggingface.co/Helsinki-NLP/opus-mt-mul-en) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8306
- Bleu: 27.1218

## 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: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results



### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.2
- Datasets 1.18.3
- Tokenizers 0.11.0

{"license": "apache-2.0", "tags": ["translation", "generated_from_trainer"], "metrics": ["bleu"], "model-index": [{"name": "model_zu-en_updated", "results": []}]}
transformers pytorch tensorboard marian text2text-generation translation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #marian #text2text-generation #translation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 




# model_zu-en_updated

This model is a fine-tuned version of Helsinki-NLP/opus-mt-mul-en on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8306
- Bleu: 27.1218

## 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: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results



### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.2
- Datasets 1.18.3
- Tokenizers 0.11.0

# model_zu-en_updated

This model is a fine-tuned version of Helsinki-NLP/opus-mt-mul-en on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8306
- Bleu: 27.1218 ## 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: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3 ### Training results ### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.2
- Datasets 1.18.3
- Tokenizers 0.11.0
TAGS
#transformers #pytorch #tensorboard #marian #text2text-generation #translation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 # model_zu-en_updated

This model is a fine-tuned version of Helsinki-NLP/opus-mt-mul-en on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8306
- Bleu: 27.1218 ## 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: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3 ### Training results ### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.2
- Datasets 1.18.3
- Tokenizers 0.11.0
passage: TAGS
#transformers #pytorch #tensorboard #marian #text2text-generation #translation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
# model_zu-en_updated

This model is a fine-tuned version of Helsinki-NLP/opus-mt-mul-en on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8306
- Bleu: 27.1218## 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: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3### Training results### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.2
- Datasets 1.18.3
- Tokenizers 0.11.0