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whisper-tiny-pure – AI Model by devkyle | AlphaNeural AI
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whisper-tiny-pure
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-small
finetune
apache-2.0
endpoints_compatible
us
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whisper-small-akan
This model is a fine-tuned version of
openai/whisper-small
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.1252
Wer: 48.2062
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: 0.0001
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: 2000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.1053
10.0
500
0.9054
55.8896
0.0202
20.0
1000
1.0748
53.0428
0.0023
30.0
1500
1.1104
48.8017
0.0003
40.0
2000
1.1252
48.2062
Framework versions
Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 3.0.0
Tokenizers 0.19.1
