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whisper_checkpoints6 – AI Model by tmtms | AlphaNeural AI
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whisper_checkpoints6
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
endpoints_compatible
us
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whisper_checkpoints6
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.2877
Wer: 23.6973
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: 24
eval_batch_size: 8
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: 4000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.009
2.5510
1000
0.0302
0.0380
0.1874
6.3291
2000
0.2390
34.0874
0.111
9.4937
3000
0.2581
29.7236
0.0599
12.6582
4000
0.2877
23.6973
Framework versions
Transformers 4.48.3
Pytorch 2.5.1+cu124
Datasets 3.3.2
Tokenizers 0.21.0
