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whisper-small-yo_ng – AI Model by ephm3ral | AlphaNeural AI
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whisper-small-yo_ng
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
fleurs
model-index
endpoints_compatible
us
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whisper-small-yo_ng
This model was trained from scratch on the fleurs dataset. It achieves the following results on the evaluation set:
Loss: 2.7203
Wer: 76.5287
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: 16
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: constant_with_warmup
lr_scheduler_warmup_steps: 50
training_steps: 2000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.027
10.0
500
2.2439
75.7976
0.0089
20.0
1000
2.3817
73.8661
0.006
30.0
1500
2.4194
73.1847
0.0057
40.0
2000
2.7203
76.5287
Framework versions
Transformers 4.52.4
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1
