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jarvis-whisper-small – AI Model by Zoroagon | AlphaNeural AI
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jarvis-whisper-small
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-small
finetune
apache-2.0
endpoints_compatible
us
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jarvis-whisper-small
This model is a fine-tuned version of
openai/whisper-small
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.6699
Wer: 23.188
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: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 16
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: 50
training_steps: 500
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
9.7220
5.5755
100
2.5188
109.058
4.4316
11.1151
200
0.6531
23.913
0.0738
16.6906
300
0.6283
21.377
0.0052
22.2302
400
0.6671
23.188
0.0005
27.8058
500
0.6699
23.188
Framework versions
Transformers 5.12.1
Pytorch 2.11.0+cu128
Datasets 5.0.0
Tokenizers 0.22.2
