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# finetuned-mbart-large-10epoch

This model is a fine-tuned version of [facebook/mbart-large-cc25](https://huggingface.co/facebook/mbart-large-cc25) on the wmt16 ro-en dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6032

## 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: 5e-05
- train_batch_size: 12
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0

### Training results



### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1

{"language": ["en", "ro"], "tags": ["generated_from_trainer"], "datasets": ["wmt16"], "model-index": [{"name": "finetuned-mbart-large-10epoch", "results": []}]}
transformers pytorch mbart text2text-generation generated_from_trainer en ro dataset:wmt16 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #mbart #text2text-generation #generated_from_trainer #en #ro #dataset-wmt16 #autotrain_compatible #endpoints_compatible #region-us 




# finetuned-mbart-large-10epoch

This model is a fine-tuned version of facebook/mbart-large-cc25 on the wmt16 ro-en dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6032

## 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: 5e-05
- train_batch_size: 12
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0

### Training results



### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1

# finetuned-mbart-large-10epoch

This model is a fine-tuned version of facebook/mbart-large-cc25 on the wmt16 ro-en dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6032 ## 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: 5e-05
- train_batch_size: 12
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0 ### Training results ### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #mbart #text2text-generation #generated_from_trainer #en #ro #dataset-wmt16 #autotrain_compatible #endpoints_compatible #region-us 
 # finetuned-mbart-large-10epoch

This model is a fine-tuned version of facebook/mbart-large-cc25 on the wmt16 ro-en dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6032 ## 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: 5e-05
- train_batch_size: 12
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0 ### Training results ### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #mbart #text2text-generation #generated_from_trainer #en #ro #dataset-wmt16 #autotrain_compatible #endpoints_compatible #region-us 
# finetuned-mbart-large-10epoch

This model is a fine-tuned version of facebook/mbart-large-cc25 on the wmt16 ro-en dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6032## 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: 5e-05
- train_batch_size: 12
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0### Training results### Framework versions

- Transformers 4.20.1
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1