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whisper-small-defined-dot-ai-qc-fr-combined-dataset-normalized – AI Model by jwkritchie | AlphaNeural AI
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whisper-small-defined-dot-ai-qc-fr-combined-dataset-normalized
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transformers
pytorch
tensorboard
whisper
automatic-speech-recognition
whisper-event
generated_from_trainer
fr
mozilla-foundation/common_voice_11_0
cc-by-nc-4.0
model-index
endpoints_compatible
us
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Whisper Small Finetuned on Defined.AI Quebec Combined French Dataset w/ Normalization
This model is a fine-tuned version of
openai/whisper-small
on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
Loss: 0.6003
Wer: 32.1540
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: 32
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 1500
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.8114
0.33
500
0.6132
32.0207
0.8052
0.67
1000
0.5988
30.2386
0.7627
1.0
1500
0.6003
32.1540
Framework versions
Transformers 4.26.0.dev0
Pytorch 1.13.1+cu117
Datasets 2.7.1.dev0
Tokenizers 0.13.2
