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# Whisper Small KR - BYoussef

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Zeroth-Korean 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 3000
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.12.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
{"language": ["ko"], "license": "apache-2.0", "tags": ["hf-asr-leaderboard", "generated_from_trainer"], "datasets": ["Bingsu/zeroth-korean"], "metrics": ["wer"], "base_model": "openai/whisper-small", "model-index": [{"name": "Whisper Small KR - BYoussef", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Bingsu/zeroth-korean", "type": "Bingsu/zeroth-korean"}, "metrics": [{"type": "wer", "value": 37.95, "name": "Wer"}]}]}]}
transformers pytorch tensorboard whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer ko dataset:Bingsu/zeroth-korean base_model:openai/whisper-small license:apache-2.0 model-index endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #hf-asr-leaderboard #generated_from_trainer #ko #dataset-Bingsu/zeroth-korean #base_model-openai/whisper-small #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us 




# Whisper Small KR - BYoussef

This model is a fine-tuned version of openai/whisper-small on the Zeroth-Korean 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 3000
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.12.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
# Whisper Small KR - BYoussef

This model is a fine-tuned version of openai/whisper-small on the Zeroth-Korean 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 3000
- mixed_precision_training: Native AMP ### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.12.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #hf-asr-leaderboard #generated_from_trainer #ko #dataset-Bingsu/zeroth-korean #base_model-openai/whisper-small #license-apache-2.0 #model-index #endpoints_compatible #has_space #region-us 
 # Whisper Small KR - BYoussef

This model is a fine-tuned version of openai/whisper-small on the Zeroth-Korean 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 3000
- mixed_precision_training: Native AMP ### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.12.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2