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whisper-kaggle-be3 – AI Model by astrung | AlphaNeural AI
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astrung
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whisper-kaggle-be3
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transformers
pytorch
whisper
automatic-speech-recognition
generated_from_trainer
audiofolder
openai/whisper-small
finetune
apache-2.0
model-index
endpoints_compatible
us
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whisper-kaggle-be3
This model is a fine-tuned version of
openai/whisper-small
on the audiofolder dataset. It achieves the following results on the evaluation set:
Loss: 0.3213
Wer: 45.6094
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
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0749
3.15
1000
0.1886
50.9273
0.0117
6.31
2000
0.2440
47.2937
0.0014
9.46
3000
0.2978
45.8933
0.0003
12.62
4000
0.3213
45.6094
Framework versions
Transformers 4.33.0.dev0
Pytorch 2.0.0
Datasets 2.14.4.dev0
Tokenizers 0.13.3
