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# wav2vec2_spoof_dection1

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the asvspoof2019 dataset.

## 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: 3e-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_ratio: 0.1
- num_epochs: 500

### Framework versions

- Transformers 4.28.1
- Pytorch 1.13.1
- Datasets 2.11.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["asvspoof2019"], "model-index": [{"name": "wav2vec2_spoof_dection1", "results": []}]}
transformers pytorch tensorboard wav2vec2 audio-classification generated_from_trainer dataset:asvspoof2019 license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #audio-classification #generated_from_trainer #dataset-asvspoof2019 #license-apache-2.0 #endpoints_compatible #region-us 




# wav2vec2_spoof_dection1

This model is a fine-tuned version of facebook/wav2vec2-base on the asvspoof2019 dataset.

## 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: 3e-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_ratio: 0.1
- num_epochs: 500

### Framework versions

- Transformers 4.28.1
- Pytorch 1.13.1
- Datasets 2.11.0
- Tokenizers 0.12.1

# wav2vec2_spoof_dection1

This model is a fine-tuned version of facebook/wav2vec2-base on the asvspoof2019 dataset. ## 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: 3e-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_ratio: 0.1
- num_epochs: 500 ### Framework versions

- Transformers 4.28.1
- Pytorch 1.13.1
- Datasets 2.11.0
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #audio-classification #generated_from_trainer #dataset-asvspoof2019 #license-apache-2.0 #endpoints_compatible #region-us 
 # wav2vec2_spoof_dection1

This model is a fine-tuned version of facebook/wav2vec2-base on the asvspoof2019 dataset. ## 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: 3e-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_ratio: 0.1
- num_epochs: 500 ### Framework versions

- Transformers 4.28.1
- Pytorch 1.13.1
- Datasets 2.11.0
- Tokenizers 0.12.1