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whisper-large-cq – AI Model by bnqwhg | AlphaNeural AI
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Whisper Large Cq
This model is a fine-tuned version of
openai/whisper-large-v3
on the hfdataset dataset. It achieves the following results on the evaluation set:
Loss: 1.5218
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-05
train_batch_size: 4
eval_batch_size: 1
seed: 42
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: 500
training_steps: 500
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0
166.6667
500
1.5218
100.0
Framework versions
Transformers 4.52.0
Pytorch 2.8.0+cu126
Datasets 3.6.0
Tokenizers 0.21.4
