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# translation-en-pt-t5-Duolingo-Subtitles

This model is a fine-tuned version of [unicamp-dl/translation-en-pt-t5](https://huggingface.co/unicamp-dl/translation-en-pt-t5) on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.7469
- eval_bleu: 39.9403
- eval_gen_len: 8.98
- eval_runtime: 997.6641
- eval_samples_per_second: 150.351
- eval_steps_per_second: 4.699
- epoch: 0.49
- step: 56000

## 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: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.13.0
- Pytorch 1.10.0+cu111
- Datasets 1.16.1
- Tokenizers 0.10.3

{"tags": ["generated_from_trainer"], "model-index": [{"name": "translation-en-pt-t5-Duolingo-Subtitles", "results": []}]}
transformers pytorch tensorboard t5 text2text-generation generated_from_trainer autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 




# translation-en-pt-t5-Duolingo-Subtitles

This model is a fine-tuned version of unicamp-dl/translation-en-pt-t5 on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.7469
- eval_bleu: 39.9403
- eval_gen_len: 8.98
- eval_runtime: 997.6641
- eval_samples_per_second: 150.351
- eval_steps_per_second: 4.699
- epoch: 0.49
- step: 56000

## 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: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.13.0
- Pytorch 1.10.0+cu111
- Datasets 1.16.1
- Tokenizers 0.10.3

# translation-en-pt-t5-Duolingo-Subtitles

This model is a fine-tuned version of unicamp-dl/translation-en-pt-t5 on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.7469
- eval_bleu: 39.9403
- eval_gen_len: 8.98
- eval_runtime: 997.6641
- eval_samples_per_second: 150.351
- eval_steps_per_second: 4.699
- epoch: 0.49
- step: 56000 ## 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: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP ### Framework versions

- Transformers 4.13.0
- Pytorch 1.10.0+cu111
- Datasets 1.16.1
- Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # translation-en-pt-t5-Duolingo-Subtitles

This model is a fine-tuned version of unicamp-dl/translation-en-pt-t5 on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.7469
- eval_bleu: 39.9403
- eval_gen_len: 8.98
- eval_runtime: 997.6641
- eval_samples_per_second: 150.351
- eval_steps_per_second: 4.699
- epoch: 0.49
- step: 56000 ## 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: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP ### Framework versions

- Transformers 4.13.0
- Pytorch 1.10.0+cu111
- Datasets 1.16.1
- Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# translation-en-pt-t5-Duolingo-Subtitles

This model is a fine-tuned version of unicamp-dl/translation-en-pt-t5 on an unknown dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.7469
- eval_bleu: 39.9403
- eval_gen_len: 8.98
- eval_runtime: 997.6641
- eval_samples_per_second: 150.351
- eval_steps_per_second: 4.699
- epoch: 0.49
- step: 56000## 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: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP### Framework versions

- Transformers 4.13.0
- Pytorch 1.10.0+cu111
- Datasets 1.16.1
- Tokenizers 0.10.3