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Whisper-Anuj-small-Odia-final – AI Model by Anujgr8 | AlphaNeural AI
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Whisper-Anuj-small-Odia-final
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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-Anuj-small-Odia-final
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: 0.1031
Wer: 43.2742
Cer: 24.0740
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: 6
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 24
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 1800
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
Cer
0.0352
4.7244
600
0.0984
41.3566
16.3829
0.0024
9.4488
1200
0.1041
49.1414
27.9848
0.0002
14.1732
1800
0.1031
43.2742
24.0740
Framework versions
Transformers 4.42.3
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1
