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whisper-classroom-kn-hi-en – AI Model by udayakumar8214 | AlphaNeural AI
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whisper-classroom-kn-hi-en
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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-classroom-kn-hi-en
This model is a fine-tuned version of
openai/whisper-small
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.1434
Wer: 196.67
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: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 100
training_steps: 2000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.4419
0.0508
500
0.2144
158.98
0.3533
0.1016
1000
0.1704
170.95
0.2945
0.1524
1500
0.1517
192.43
0.2854
0.2032
2000
0.1434
196.67
Framework versions
Transformers 5.0.0
Pytorch 2.10.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2
