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whisper-small-es7000 – AI Model by jessicadiveai | AlphaNeural AI
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whisper-small-es7000
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
hi
openai/whisper-small
finetune
apache-2.0
endpoints_compatible
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Whisper Small Hi - Sanchit Gandhi
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: 0.2829
Wer: 13.5962
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: 50
training_steps: 400
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.3389
0.2747
100
0.3355
16.9866
0.3073
0.5495
200
0.3035
14.1808
0.2915
0.8242
300
0.2884
15.7916
0.2597
1.0989
400
0.2829
13.5962
Framework versions
Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.0
Tokenizers 0.19.1
