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whisper-small-custom-300 – AI Model by lyhourt | AlphaNeural AI
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whisper-small-custom-300
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-small
finetune
apache-2.0
endpoints_compatible
us
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Whisper Small custom 3000
This model is a fine-tuned version of
openai/whisper-small
on the lyhourt/clean dataset. It achieves the following results on the evaluation set:
Loss: 0.0304
Wer: 4.6902
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: 64
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
training_steps: 300
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0783
0.3333
100
0.0938
11.8124
0.0513
0.6667
200
0.0689
8.2224
0.0027
1.19
300
0.0304
4.6902
Framework versions
Transformers 4.41.0
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.19.1
