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whisper-ckm-4 – AI Model by ninninz | AlphaNeural AI
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whisper-ckm-4
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
audiofolder
openai/whisper-large-v3
finetune
apache-2.0
model-index
endpoints_compatible
us
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whisper-large-v3-croarian_10
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: 2.1025
Wer: 91.7516
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: 4000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0795
10.87
1000
1.6251
88.0094
0.0162
21.74
2000
1.8668
126.1658
0.0066
32.61
3000
2.0541
104.8295
0.0042
43.48
4000
2.1025
91.7516
Framework versions
Transformers 4.37.1
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.1
