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whisper-small-finetuned-v4en – AI Model by shull | AlphaNeural AI
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whisper-small-finetuned-v4en
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
en
openai/whisper-small
finetune
apache-2.0
endpoints_compatible
us
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Whisper small v4-en finetuned
This model is a fine-tuned version of
openai/whisper-small
on the my_audio_dataset dataset. It achieves the following results on the evaluation set:
Loss: 0.1696
Wer: 5.1242
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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 300
training_steps: 3000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.1015
8.7336
1000
0.1437
5.0065
0.0011
17.4672
2000
0.1643
5.1503
0.0004
26.2009
3000
0.1696
5.1242
Framework versions
Transformers 4.40.2
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.19.1
