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Whisper Medium

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

Loss: 0.2798
Wer: 21.2425

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: 50
training_steps: 250
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
2.4644	1.0417	50	6.2039	73.7475
3.2455	2.0833	100	0.3363	23.6473
0.1546	3.125	150	0.2708	20.8417
0.0685	4.1667	200	0.2790	19.8397
0.0427	5.2083	250	0.2798	21.2425

Framework versions

PEFT 0.12.0
Transformers 4.43.4
Pytorch 2.2.0
Datasets 2.20.0
Tokenizers 0.19.1

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Dataset used to train miosipov/asr_medium_augmented_v2

Evaluation results

Wer on b-brave/speech_disorders_voice
self-reported

21.242