Pravalika56
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my_model_directory

Automatic Speech Recognition

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Whisper Small te - Pravalika Bollam

This model is a fine-tuned version of openai/whisper-small on the Common Voice 16 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: 2e-05
train_batch_size: 16
eval_batch_size: 32
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: 60
training_steps: 200
mixed_precision_training: Native AMP

Training results

Framework versions

Transformers 4.41.0.dev0
Pytorch 2.2.1+cu121
Datasets 2.19.0
Tokenizers 0.19.1

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Safetensors

Model size

242M params

Tensor type

F32

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Automatic Speech Recognition

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Base model

openai/whisper-small

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(1874)

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Dataset used to train Pravalika56/my_model_directory

Evaluation results

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