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Whisper Large v3

This model is a fine-tuned version of openai/whisper-large-v3 on the b-brave/speech_disorders_voice dataset. It achieves the following results on the evaluation set:

Loss: 0.3055
Wer: 23.5174

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: 0.001
train_batch_size: 32
eval_batch_size: 16
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: 128
training_steps: 256
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.3683	0.9481	64	0.3394	19.8364
0.1165	1.8963	128	0.3326	15.3374
0.0332	2.8444	192	0.3112	19.6319
0.013	3.7926	256	0.3055	23.5174

Framework versions

PEFT 0.12.0
Transformers 4.44.2
Pytorch 2.2.0
Datasets 2.21.0
Tokenizers 0.19.1

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Dataset used to train miosipov/asr_large_v3.2b_augmented

Evaluation results

Wer on b-brave/speech_disorders_voice
self-reported

23.517