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whisper-small-finetuned – AI Model by shane062 | AlphaNeural AI
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shane062
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whisper-small-finetuned
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
audiofolder
openai/whisper-small
finetune
apache-2.0
model-index
endpoints_compatible
us
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whisper-small-finetuned
This model is a fine-tuned version of
openai/whisper-small
on the audiofolder dataset. It achieves the following results on the evaluation set:
Loss: 0.8410
Wer Ortho: 67.5676
Wer: 67.5676
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: constant_with_warmup
lr_scheduler_warmup_steps: 10
training_steps: 100
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer Ortho
Wer
0.7732
16.6667
50
1.3685
70.2703
70.2703
0.0005
33.3333
100
0.8410
67.5676
67.5676
Framework versions
Transformers 4.41.1
Pytorch 2.3.0+cpu
Datasets 2.19.1
Tokenizers 0.19.1
