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whisper-small-bn – AI Model by Aranya31 | AlphaNeural AI
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Aranya31
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whisper-small-bn
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
bn
mozilla-foundation/common_voice_11_0
openai/whisper-small
finetune
apache-2.0
model-index
endpoints_compatible
us
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whisper_small_bn_Aranya_ACI
This model is a fine-tuned version of
openai/whisper-small
on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
Loss: 0.5506
Wer: 60.4588
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 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: 10
training_steps: 1000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0103
3.1746
200
0.4097
61.8241
0.0039
6.3492
400
0.4771
62.8072
0.0009
9.5238
600
0.5293
60.3495
0.0003
12.6984
800
0.5462
60.2949
0.0002
15.8730
1000
0.5506
60.4588
Framework versions
Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1
