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whisper-medium-tachebdant – AI Model by iukocha | AlphaNeural AI
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whisper-medium-tachebdant
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
ar
openai/whisper-medium
finetune
apache-2.0
endpoints_compatible
us
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Whisper Medium Tachebdant
This model is a fine-tuned version of
openai/whisper-medium
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.6922
Wer: 55.0562
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_FUSED 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: 50
training_steps: 200
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0013
11.7647
200
0.6922
55.0562
Framework versions
Transformers 5.8.0
Pytorch 2.10.0+cu128
Datasets 4.8.5
Tokenizers 0.22.2
