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whisper-tiny-medium-fa-kaggle – AI Model by momirDev | AlphaNeural AI
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whisper-tiny-medium-fa-kaggle
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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-medium-fa-kaggle
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: 0.1275
Wer: 0.1595
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: 64
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 256
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: 20
training_steps: 250
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.2217
0.9479
50
0.2045
0.2632
0.1617
1.8910
100
0.1605
0.2172
0.1326
2.8341
150
0.1404
0.1806
0.1173
3.7773
200
0.1307
0.1622
0.111
4.7204
250
0.1275
0.1595
Framework versions
Transformers 4.48.3
Pytorch 2.5.1+cu124
Datasets 3.3.2
Tokenizers 0.21.0
