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# wav2vec2-common_voice-ab-demo

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the COMMON_VOICE - AB dataset.
It achieves the following results on the evaluation set:
- Loss: 15.1812
- Wer: 1.0

## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 32
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 15.0
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.11.0.dev0
- Pytorch 1.9.0+cu111
- Datasets 1.12.1
- Tokenizers 0.10.3

{"language": ["ab"], "license": "apache-2.0", "tags": ["speech-recognition", "common_voice", "generated_from_trainer"], "model-index": [{"name": "wav2vec2-common_voice-ab-demo", "results": []}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition speech-recognition common_voice generated_from_trainer ab license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #speech-recognition #common_voice #generated_from_trainer #ab #license-apache-2.0 #endpoints_compatible #region-us 




# wav2vec2-common_voice-ab-demo

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the COMMON_VOICE - AB dataset.
It achieves the following results on the evaluation set:
- Loss: 15.1812
- Wer: 1.0

## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 32
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 15.0
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.11.0.dev0
- Pytorch 1.9.0+cu111
- Datasets 1.12.1
- Tokenizers 0.10.3

# wav2vec2-common_voice-ab-demo

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the COMMON_VOICE - AB dataset.
It achieves the following results on the evaluation set:
- Loss: 15.1812
- Wer: 1.0 ## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 32
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 15.0
- mixed_precision_training: Native AMP ### Training results ### Framework versions

- Transformers 4.11.0.dev0
- Pytorch 1.9.0+cu111
- Datasets 1.12.1
- Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #speech-recognition #common_voice #generated_from_trainer #ab #license-apache-2.0 #endpoints_compatible #region-us 
 # wav2vec2-common_voice-ab-demo

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the COMMON_VOICE - AB dataset.
It achieves the following results on the evaluation set:
- Loss: 15.1812
- Wer: 1.0 ## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 32
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 15.0
- mixed_precision_training: Native AMP ### Training results ### Framework versions

- Transformers 4.11.0.dev0
- Pytorch 1.9.0+cu111
- Datasets 1.12.1
- Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #speech-recognition #common_voice #generated_from_trainer #ab #license-apache-2.0 #endpoints_compatible #region-us 
# wav2vec2-common_voice-ab-demo

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the COMMON_VOICE - AB dataset.
It achieves the following results on the evaluation set:
- Loss: 15.1812
- Wer: 1.0## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 32
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 15.0
- mixed_precision_training: Native AMP### Training results### Framework versions

- Transformers 4.11.0.dev0
- Pytorch 1.9.0+cu111
- Datasets 1.12.1
- Tokenizers 0.10.3