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whisper-medium-ml – AI Model by Abdulvajid | AlphaNeural AI
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whisper-medium-ml
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
hf-asr-leaderboard
generated_from_trainer
lt
mozilla-foundation/common_voice_17_0
openai/whisper-medium
finetune
apache-2.0
endpoints_compatible
us
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Whisper Medium - Malayalam
This model is a fine-tuned version of
openai/whisper-medium
on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
eval_loss: 0.2084
eval_wer: 71.3595
eval_runtime: 761.8206
eval_samples_per_second: 0.932
eval_steps_per_second: 0.117
epoch: 4.7244
step: 600
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 OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
training_steps: 1000
mixed_precision_training: Native AMP
Framework versions
Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1
