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whisper-medium-hi – AI Model by Aakali | AlphaNeural AI
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Aakali
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whisper-medium-hi
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
hi
mozilla-foundation/common_voice_11_0
openai/whisper-medium
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper medium Hi - Aa
This model is a fine-tuned version of
openai/whisper-medium
on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
Loss: 0.3556
Wer: 24.2275
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
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
Wer
0.0564
2.4450
1000
0.2346
26.9153
0.0159
4.8900
2000
0.2877
26.1619
0.0026
7.3350
3000
0.3198
24.9471
0.0002
9.7800
4000
0.3457
24.8074
0.0001
12.2249
5000
0.3556
24.2275
Framework versions
Transformers 4.41.0
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.19.1
