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rao-vandromme-purcell-distil-finetuned – AI Model by GregoryVandromme | AlphaNeural AI
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GregoryVandromme
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rao-vandromme-purcell-distil-finetuned
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
distil-whisper/distil-large-v2
finetune
mit
endpoints_compatible
us
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rao-vandromme-purcell-distil-finetuned
This model is a fine-tuned version of
distil-whisper/distil-large-v2
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0590
Wer: 2.9688
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: 5
training_steps: 50
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.6205
0.29
10
0.2496
3.4375
0.073
0.59
20
0.0745
2.5
0.2899
0.88
30
0.0647
3.125
0.034
1.18
40
0.0674
3.2812
0.0507
1.47
50
0.0590
2.9688
Framework versions
Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0
