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whisper-fleurs-medium-te_in – AI Model by jonahdvt | AlphaNeural AI
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whisper-fleurs-medium-te_in
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
te
google/fleurs
openai/whisper-medium
finetune
apache-2.0
endpoints_compatible
us
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Whisper Medium FLEURS – te FLEURS Fine‑tuning
This model is a fine-tuned version of
openai/whisper-medium
on the FLEURS dataset.
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: 4
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: 100
num_epochs: 10
mixed_precision_training: Native AMP
Training results
Framework versions
Transformers 4.48.3
Pytorch 2.6.0+cu124
Datasets 3.3.2
Tokenizers 0.21.0
