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wosota-asr-medium-v1 – AI Model by mogu98 | AlphaNeural AI
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wosota-asr-medium-v1
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-medium
finetune
apache-2.0
endpoints_compatible
us
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wosota-asr-medium-v1
This model is a fine-tuned version of
openai/whisper-medium
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.9563
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: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 5000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
0.5216
1.0546
1000
0.7874
0.1898
2.1092
2000
0.8209
0.0491
4.0184
3000
0.8889
0.0220
5.073
4000
0.9264
0.0051
6.1276
5000
0.9563
Framework versions
Transformers 5.6.0.dev0
Pytorch 2.10.0+cu128
Datasets 2.16.0
Tokenizers 0.22.2
