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# Whisper Tiny En - Abhishek Singh

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 13.0 dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.5896
- eval_wil: 42.8626
- eval_runtime: 1949.885
- eval_samples_per_second: 5.129
- eval_steps_per_second: 0.641
- epoch: 0.05
- step: 24000

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 500000
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.29.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

{"language": ["en"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["mozilla-foundation/common_voice_13_0"], "model-index": [{"name": "Whisper Tiny En - Abhishek Singh", "results": []}]}
transformers pytorch tensorboard whisper automatic-speech-recognition generated_from_trainer en dataset:mozilla-foundation/common_voice_13_0 license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #generated_from_trainer #en #dataset-mozilla-foundation/common_voice_13_0 #license-apache-2.0 #endpoints_compatible #region-us 




# Whisper Tiny En - Abhishek Singh

This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 13.0 dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.5896
- eval_wil: 42.8626
- eval_runtime: 1949.885
- eval_samples_per_second: 5.129
- eval_steps_per_second: 0.641
- epoch: 0.05
- step: 24000

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 500000
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.29.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

# Whisper Tiny En - Abhishek Singh

This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 13.0 dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.5896
- eval_wil: 42.8626
- eval_runtime: 1949.885
- eval_samples_per_second: 5.129
- eval_steps_per_second: 0.641
- epoch: 0.05
- step: 24000 ## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 500000
- mixed_precision_training: Native AMP ### Framework versions

- Transformers 4.29.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #generated_from_trainer #en #dataset-mozilla-foundation/common_voice_13_0 #license-apache-2.0 #endpoints_compatible #region-us 
 # Whisper Tiny En - Abhishek Singh

This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 13.0 dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.5896
- eval_wil: 42.8626
- eval_runtime: 1949.885
- eval_samples_per_second: 5.129
- eval_steps_per_second: 0.641
- epoch: 0.05
- step: 24000 ## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 500000
- mixed_precision_training: Native AMP ### Framework versions

- Transformers 4.29.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #whisper #automatic-speech-recognition #generated_from_trainer #en #dataset-mozilla-foundation/common_voice_13_0 #license-apache-2.0 #endpoints_compatible #region-us 
# Whisper Tiny En - Abhishek Singh

This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 13.0 dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.5896
- eval_wil: 42.8626
- eval_runtime: 1949.885
- eval_samples_per_second: 5.129
- eval_steps_per_second: 0.641
- epoch: 0.05
- step: 24000## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 500000
- mixed_precision_training: Native AMP### Framework versions

- Transformers 4.29.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3