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whisper-tiny-mn – AI Model by lkhagvaa12 | AlphaNeural AI
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whisper-tiny-mn
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-tiny
finetune
apache-2.0
endpoints_compatible
us
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Whisper tiny
This model is a fine-tuned version of
openai/whisper-tiny
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.4842
Wer Ortho: 60.9132
Wer: 60.9029
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: 32
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 Ortho
Wer
1.0053
1.5198
500
0.6511
72.9011
72.8777
0.7337
3.0395
1000
0.5380
65.5752
65.5485
0.5557
4.5593
1500
0.4971
63.5066
63.4855
0.3969
6.0790
2000
0.4842
60.9132
60.9029
Framework versions
Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.2
