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whisper-medium-ft-custom – AI Model by UsmanAXAI | AlphaNeural AI
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whisper-medium-ft-custom
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
ar-asr-leaderboard
generated_from_trainer
ar
mozilla-foundation/common_voice_16_1
openai/whisper-medium
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper Medium Ar - AxAI
This model is a fine-tuned version of
openai/whisper-medium
on the Common Voice 16.1 dataset. It achieves the following results on the evaluation set:
Loss: 1.4298
Wer: 100.0
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-06
train_batch_size: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 1000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0045
35.71
500
1.3081
100.0
0.0012
71.43
1000
1.4298
100.0
Framework versions
Transformers 4.37.2
Pytorch 2.2.0+cu121
Datasets 2.17.1
Tokenizers 0.15.2
