This model is a fine-tuned version of openai/whisper-small on the Even Speech Biblical dataset. It achieves the following results on the evaluation set:

Loss: 0.4591
Wer: 53.8802

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: 8
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: 300
training_steps: 2000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.05	5.9880	500	0.3920	63.7525
0.0022	11.9760	1000	0.4307	57.3674
0.0003	17.9641	1500	0.4528	51.7682
0.0003	23.9521	2000	0.4591	53.8802

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1

tanya-kta/whisper-small-even

Whisper Small Even - Sanchit Gandhi

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

tanya-kta/
whisper-small-even