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whisper-small-tuning – AI Model by syjung | AlphaNeural AI

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syjung/
whisper-small-tuning

like

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automatic-speech-recognition

hf-asr-leaderboard

generated_from_trainer

mozilla-foundation/common_voice_11_0

endpoints_compatible

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Whisper Small Hi - Sanchit Gandhi

This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

eval_loss: 7.5773
eval_wer: 99.3995
eval_runtime: 561.7733
eval_samples_per_second: 1.107
eval_steps_per_second: 1.107
epoch: 0.01
step: 20

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: 1
eval_batch_size: 1
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
training_steps: 40
mixed_precision_training: Native AMP

Framework versions

Transformers 4.27.0.dev0
Pytorch 1.13.1+cu117
Datasets 2.8.0
Tokenizers 0.13.2