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whisper-ckm-1 – AI Model by ninninz | AlphaNeural AI
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whisper-ckm-1
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
cr
audiofolder
openai/whisper-large-v3
finetune
apache-2.0
model-index
endpoints_compatible
us
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whisper-large-v3-croatian-v3
This model is a fine-tuned version of
openai/whisper-large-v3
on the audiofolder dataset. It achieves the following results on the evaluation set:
Loss: 2.8726
Wer: 74.3118
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: 1.25e-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: 4000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0539
13.89
1000
2.3264
87.0594
0.0116
27.78
2000
2.5778
91.6517
0.0072
41.67
3000
2.8216
76.4729
0.0074
55.56
4000
2.8726
74.3118
Framework versions
Transformers 4.36.1
Pytorch 2.1.1+cu121
Datasets 2.15.0
Tokenizers 0.15.0
