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# unicamp-finetuned-en-to-pt-dataset-ted

This model is a fine-tuned version of [unicamp-dl/translation-pt-en-t5](https://huggingface.co/unicamp-dl/translation-pt-en-t5) on the ted_iwlst2013 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8861
- Bleu: 25.6503

## 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
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1

{"tags": ["translation", "generated_from_trainer"], "datasets": ["ted_iwlst2013"], "metrics": ["bleu"], "model-index": [{"name": "unicamp-finetuned-en-to-pt-dataset-ted", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "ted_iwlst2013", "type": "ted_iwlst2013", "args": "en-pt"}, "metrics": [{"type": "bleu", "value": 25.65030250145235, "name": "Bleu"}]}]}]}
transformers pytorch tensorboard t5 text2text-generation translation generated_from_trainer dataset:ted_iwlst2013 model-index autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #translation #generated_from_trainer #dataset-ted_iwlst2013 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 




# unicamp-finetuned-en-to-pt-dataset-ted

This model is a fine-tuned version of unicamp-dl/translation-pt-en-t5 on the ted_iwlst2013 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8861
- Bleu: 25.6503

## 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
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1

# unicamp-finetuned-en-to-pt-dataset-ted

This model is a fine-tuned version of unicamp-dl/translation-pt-en-t5 on the ted_iwlst2013 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8861
- Bleu: 25.6503 ## 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
- mixed_precision_training: Native AMP ### Training results ### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #translation #generated_from_trainer #dataset-ted_iwlst2013 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # unicamp-finetuned-en-to-pt-dataset-ted

This model is a fine-tuned version of unicamp-dl/translation-pt-en-t5 on the ted_iwlst2013 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8861
- Bleu: 25.6503 ## 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
- mixed_precision_training: Native AMP ### Training results ### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #translation #generated_from_trainer #dataset-ted_iwlst2013 #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# unicamp-finetuned-en-to-pt-dataset-ted

This model is a fine-tuned version of unicamp-dl/translation-pt-en-t5 on the ted_iwlst2013 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8861
- Bleu: 25.6503## 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
- mixed_precision_training: Native AMP### Training results### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1