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whisper_base_it – AI Model by dearyoungjo | AlphaNeural AI
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whisper_base_it
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
it
mozilla-foundation/common_voice_17_0
openai/whisper-base
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper Small Hi - Sanchit Gandhi
This model is a fine-tuned version of
openai/whisper-base
on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
Loss: 1.1530
Wer: 41.2624
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: 2
training_steps: 4
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.9703
0.0159
1
1.1724
42.1492
1.0107
0.0317
2
1.1724
42.1492
1.1515
0.0476
3
1.1724
42.1492
0.843
0.0635
4
1.1530
41.2624
Framework versions
Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.0
Tokenizers 0.19.1
