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whisper-medium-id – AI Model by Rizka | AlphaNeural AI
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whisper-medium-id
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
id
mozilla-foundation/common_voice_11_0
openai/whisper-medium
finetune
apache-2.0
model-index
endpoints_compatible
us
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whisper-medium-id
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: 0.2226
Wer: 13.6053
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-06
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
0.2022
1.9305
1000
0.1830
13.1308
0.1089
3.8610
2000
0.1824
13.0192
0.0609
5.7915
3000
0.1949
13.2657
0.0327
7.7220
4000
0.2125
13.4797
0.0257
9.6525
5000
0.2226
13.6053
Framework versions
Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 3.0.0
Tokenizers 0.19.1
