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whisper-medium-te-v1 – AI Model by kattojuprashanth238 | AlphaNeural AI
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
te
mozilla-foundation/common_voice_17_0
openai/whisper-medium
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper Medium Te - Prashanth Kattoju
This model is a fine-tuned version of
openai/whisper-medium
on the Common Voice 17 dataset. It achieves the following results on the evaluation set:
Loss: 0.0502
Wer Ortho: 19.7802
Wer: 8.2418
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: 4
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 8
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 50
training_steps: 1500
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer Ortho
Wer
0.0147
6.4946
1500
0.0502
19.7802
8.2418
Framework versions
Transformers 4.48.3
Pytorch 2.5.1+cu124
Datasets 3.3.2
Tokenizers 0.21.0
