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# marian-finetuned-kde4-en-to-ar

This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-ar](https://huggingface.co/Helsinki-NLP/opus-mt-en-ar) on the kde4 dataset.

## Model description
if you want to learn about the model used check [Helsinki-NLP Model](https://huggingface.co/Helsinki-NLP/opus-mt-en-ar)

## Intended uses & limitations

## Training and evaluation data

More information needed

## Training procedure
the training was done on google colab.

### 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
- mixed_precision_training: Native AMP

### Training results


### Framework versions
- Transformers 4.20.0
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["translation", "generated_from_trainer"], "datasets": ["kde4"], "model-index": [{"name": "marian-finetuned-kde4-en-to-ar", "results": []}]}
transformers pytorch tensorboard marian text2text-generation translation generated_from_trainer dataset:kde4 license:apache-2.0 autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #tensorboard #marian #text2text-generation #translation #generated_from_trainer #dataset-kde4 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 




# marian-finetuned-kde4-en-to-ar

This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-ar on the kde4 dataset.

## Model description
if you want to learn about the model used check Helsinki-NLP Model

## Intended uses & limitations

## Training and evaluation data

More information needed

## Training procedure
the training was done on google colab.

### 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
- mixed_precision_training: Native AMP

### Training results


### Framework versions
- Transformers 4.20.0
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1

# marian-finetuned-kde4-en-to-ar

This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-ar on the kde4 dataset. ## Model description
if you want to learn about the model used check Helsinki-NLP Model ## Intended uses & limitations ## Training and evaluation data

More information needed ## Training procedure
the training was done on google colab. ### 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
- mixed_precision_training: Native AMP ### Training results ### Framework versions
- Transformers 4.20.0
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #marian #text2text-generation #translation #generated_from_trainer #dataset-kde4 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # marian-finetuned-kde4-en-to-ar

This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-ar on the kde4 dataset. ## Model description
if you want to learn about the model used check Helsinki-NLP Model ## Intended uses & limitations ## Training and evaluation data

More information needed ## Training procedure
the training was done on google colab. ### 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
- mixed_precision_training: Native AMP ### Training results ### Framework versions
- Transformers 4.20.0
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #marian #text2text-generation #translation #generated_from_trainer #dataset-kde4 #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
# marian-finetuned-kde4-en-to-ar

This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-ar on the kde4 dataset.## Model description
if you want to learn about the model used check Helsinki-NLP Model## Intended uses & limitations## Training and evaluation data

More information needed## Training procedure
the training was done on google colab.### 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
- mixed_precision_training: Native AMP### Training results### Framework versions
- Transformers 4.20.0
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1