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whisper-small-ta – AI Model by navin-kumar-j | AlphaNeural AI
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
ta
mozilla-foundation/common_voice_17_0
openai/whisper-small
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper Small Ta - Navin Kumar J
This model is a fine-tuned version of
openai/whisper-small
on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
Loss: 0.2155
Wer: 43.2294
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: 16
eval_batch_size: 8
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 4000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.1639
0.2773
1000
0.2724
51.7611
0.1547
0.5546
2000
0.2353
46.9249
0.1357
0.8319
3000
0.2243
44.6897
0.0967
1.1093
4000
0.2155
43.2294
Framework versions
Transformers 4.50.1
Pytorch 2.6.0+cu124
Datasets 3.4.1
Tokenizers 0.21.1
