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whisper-base-ASR-EN – AI Model by enankobh1 | AlphaNeural AI

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enankobh1/
whisper-base-ASR-EN

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automatic-speech-recognition

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whisper-base-ASR-EN

This model is a fine-tuned version of openai/whisper-base.en on the None dataset. It achieves the following results on the evaluation set:

eval_loss: 0.7074
eval_wer: 23.6824
eval_runtime: 244.0627
eval_samples_per_second: 5.507
eval_steps_per_second: 0.344
epoch: 23.81
step: 4000

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: 32
eval_batch_size: 16
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: 4000
mixed_precision_training: Native AMP

Framework versions

Transformers 4.27.0.dev0
Pytorch 1.13.1+cu116
Datasets 2.9.0
Tokenizers 0.13.2