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whisper-large-nob-ncc-s – AI Model by versae | AlphaNeural AI
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whisper-large-nob-ncc-s
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transformers
pytorch
tensorboard
safetensors
whisper
automatic-speech-recognition
whisper-event
generated_from_trainer
no
nb
NbAiLab/NCC_S
apache-2.0
model-index
endpoints_compatible
us
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Whisper Large Norwegian
This model is a fine-tuned version of
openai/whisper-large-v2
on the NbAiLab/NCC_S dataset. It achieves the following results on the evaluation set:
Loss: 0.2776
Wer: 12.5152
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: 12
eval_batch_size: 6
seed: 42
distributed_type: multi-GPU
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 5000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.6892
0.2
1000
0.3177
15.1035
0.6782
0.4
2000
0.3033
13.4592
0.6317
0.6
3000
0.2909
13.7637
0.5609
0.8
4000
0.2803
12.6675
0.5726
1.0
5000
0.2776
12.5152
Framework versions
Transformers 4.26.0.dev0
Pytorch 1.13.0+cu117
Datasets 2.7.1.dev0
Tokenizers 0.11.0
