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audio_speech_recognition-1b-ATC – AI Model by ashpandian | AlphaNeural AI
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ashpandian
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audio_speech_recognition-1b-ATC
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transformers
safetensors
whisper
automatic-speech-recognition
hf-asr-leaderboard
generated_from_trainer
en
openai/whisper-large-v3
finetune
apache-2.0
endpoints_compatible
us
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Whisper-large-v3-atc
This model is a fine-tuned version of
openai/whisper-large-v3
on the atc_dataset dataset. It achieves the following results on the evaluation set:
Loss: 0.2187
Wer: 7.4754
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: 500
training_steps: 4000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.19
0.8446
1000
0.2450
9.4369
0.1105
1.6892
2000
0.2092
8.4916
0.047
2.5338
3000
0.2069
7.9794
0.017
3.3784
4000
0.2187
7.4754
Framework versions
Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.19.2
Tokenizers 0.19.1
