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whisper-base-en – AI Model by Foxasdf | AlphaNeural AI
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whisper-base-en
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
en-asr-leaderboard
generated_from_trainer
en
mozilla-foundation/common_voice_3_0
openai/whisper-base
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper base en - spongebob
This model is a fine-tuned version of
openai/whisper-base
on the Common Voice 3.0 dataset. It achieves the following results on the evaluation set:
Loss: 0.3451
Wer: 18.3630
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: 2
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 16
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: 500
training_steps: 1500
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.2586
0.84
500
0.3588
19.4733
0.1667
1.68
1000
0.3451
17.4892
0.1069
2.53
1500
0.3451
18.3630
Framework versions
Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0
