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whisper-medium-ar-tiny – AI Model by RawandLaouini | AlphaNeural AI
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RawandLaouini
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whisper-medium-ar-tiny
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transformers
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-medium
finetune
apache-2.0
endpoints_compatible
us
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whisper-medium-ar-tiny
This model is a fine-tuned version of
openai/whisper-medium
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.0900
Wer: 36.7470
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: 2
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 4
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
lr_scheduler_warmup_steps: 10
training_steps: 100
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
1.3745
2.2222
20
1.4938
56.6265
1.1549
4.4444
40
1.2452
57.2289
1.0416
6.6667
60
1.1509
38.5542
0.9904
8.8889
80
1.1050
38.5542
0.9493
11.1111
100
1.0900
36.7470
Framework versions
Transformers 4.50.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1
