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whisper-medium-ro_common_voice – AI Model by AdaCodruta | AlphaNeural AI
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AdaCodruta
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whisper-medium-ro_common_voice
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
common_voice_17_0
openai/whisper-medium
finetune
apache-2.0
model-index
endpoints_compatible
us
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whisper-medium-ro_private_dataset
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:
Loss: 0.2179
Wer Ortho: 14.3915
Wer: 12.8568
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: 32
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
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: 50
training_steps: 1000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer Ortho
Wer
0.0039
6.2112
500
0.2024
14.7619
13.1275
0.0005
12.4224
1000
0.2179
14.3915
12.8568
Framework versions
Transformers 4.46.3
Pytorch 2.5.1+cu118
Datasets 3.1.0
Tokenizers 0.20.3
