Jungwonchang
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whisper_base.en-Full-SPGIspeech-xs

Automatic Speech Recognition

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openai/whisper-base.en, all the parameters updated for 5 epochs

This model is a fine-tuned version of openai/whisper-base.en on the 2 hour dataset of SPGIspeech(custom dataset) 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: 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: 50
training_steps: 120
mixed_precision_training: Native AMP

Training results

Framework versions

Transformers 4.36.0.dev0
Pytorch 1.12.1+cu116
Datasets 2.4.0
Tokenizers 0.15.0

Downloads last month: 11

Safetensors

Model size

72.6M params

Tensor type

F32

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Automatic Speech Recognition

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Base model

openai/whisper-base.en

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Evaluation results

WER on Test set for spgispeech
test set self-reported

8.800
CER on Test set for spgispeech
test set self-reported

2.960

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