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whisper-large-odiya – AI Model by Apocalypse-19 | AlphaNeural AI
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whisper-large-odiya
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transformers
pytorch
tensorboard
whisper
automatic-speech-recognition
generated_from_trainer
or
mozilla-foundation/common_voice_13_0
openai/whisper-large-v2
finetune
apache-2.0
model-index
endpoints_compatible
us
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whisper-large-odiya
This model is a fine-tuned version of
openai/whisper-large-v2
on the Common Voice 13 dataset. It achieves the following results on the evaluation set:
Loss: 0.2808
Wer Ortho: 45.8771
Wer: 18.4527
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: 8
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 20
training_steps: 1000
Training results
Training Loss
Epoch
Step
Validation Loss
Wer Ortho
Wer
0.0019
9.71
500
0.2362
45.4898
19.3002
0.0001
19.42
1000
0.2808
45.8771
18.4527
Framework versions
Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3
