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# SpeechT5 TTS Catalan

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the Commonvoice dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.5261
- eval_runtime: 45.091
- eval_samples_per_second: 22.177
- eval_steps_per_second: 1.397
- epoch: 8.02
- step: 4000

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 8000

### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"language": ["ca"], "license": "mit", "tags": ["TTS", "generated_from_trainer"], "datasets": ["mozilla-foundation/common_voice_11_0"], "model-index": [{"name": "SpeechT5 TTS Catalan", "results": []}]}
transformers pytorch tensorboard speecht5 text-to-audio TTS generated_from_trainer ca dataset:mozilla-foundation/common_voice_11_0 license:mit endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #speecht5 #text-to-audio #TTS #generated_from_trainer #ca #dataset-mozilla-foundation/common_voice_11_0 #license-mit #endpoints_compatible #region-us 




# SpeechT5 TTS Catalan

This model is a fine-tuned version of microsoft/speecht5_tts on the Commonvoice dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.5261
- eval_runtime: 45.091
- eval_samples_per_second: 22.177
- eval_steps_per_second: 1.397
- epoch: 8.02
- step: 4000

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 8000

### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

# SpeechT5 TTS Catalan

This model is a fine-tuned version of microsoft/speecht5_tts on the Commonvoice dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.5261
- eval_runtime: 45.091
- eval_samples_per_second: 22.177
- eval_steps_per_second: 1.397
- epoch: 8.02
- step: 4000 ## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 8000 ### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #speecht5 #text-to-audio #TTS #generated_from_trainer #ca #dataset-mozilla-foundation/common_voice_11_0 #license-mit #endpoints_compatible #region-us 
 # SpeechT5 TTS Catalan

This model is a fine-tuned version of microsoft/speecht5_tts on the Commonvoice dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.5261
- eval_runtime: 45.091
- eval_samples_per_second: 22.177
- eval_steps_per_second: 1.397
- epoch: 8.02
- step: 4000 ## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 8000 ### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3