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whisper-base.en-speech-commands-v1 – AI Model by gokulsrinivasagan | AlphaNeural AI
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gokulsrinivasagan
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whisper-base.en-speech-commands-v1
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transformers
tensorboard
safetensors
whisper
audio-classification
generated_from_trainer
speech_commands
openai/whisper-base.en
finetune
apache-2.0
model-index
endpoints_compatible
us
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whisper-base.en-speech-commands-v1
This model is a fine-tuned version of
openai/whisper-base.en
on the speech_commands dataset. It achieves the following results on the evaluation set:
Loss: 1.1638
Accuracy: 0.8067
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: 5e-05
train_batch_size: 96
eval_batch_size: 96
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 384
optimizer: Use 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_ratio: 0.1
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.3306
1.0
103
1.1388
0.8022
0.1314
2.0
206
1.1511
0.8022
0.0672
3.0
309
1.1448
0.8062
0.048
4.0
412
1.1638
0.8067
0.034
5.0
515
1.1655
0.8058
Framework versions
Transformers 4.51.2
Pytorch 2.6.0+cu126
Datasets 3.5.0
Tokenizers 0.21.1
