ap-LracgWanIBIvdjeHeDoO07

This model is a fine-tuned version of openai/whisper-large-v3-turbo on the None dataset. It achieves the following results on the evaluation set:

Model description

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The following hyperparameters were used during training:

learning_rate: 0.0003
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 64
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 400
num_epochs: 16
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Model Preparation Time	Wer
0.3835	1.0	250	0.4302	0.025	0.2568
0.3373	2.0	500	0.4448	0.025	0.1976
0.2796	3.0	750	0.3961	0.025	0.1652
0.2106	4.0	1000	0.3875	0.025	0.1811
0.1608	5.0	1250	0.3860	0.025	0.1693
0.1203	6.0	1500	0.3717	0.025	0.1520
0.0948	7.0	1750	0.3979	0.025	0.1592
0.0723	8.0	2000	0.4183	0.025	0.1511
0.0569	9.0	2250	0.4161	0.025	0.1597
0.0423	10.0	2500	0.4580	0.025	0.1540
0.031	11.0	2750	0.4652	0.025	0.1389
0.0208	12.0	3000	0.4817	0.025	0.1391
0.0162	13.0	3250	0.5002	0.025	0.1369
0.0087	14.0	3500	0.5394	0.025	0.1378
0.0033	15.0	3750	0.5667	0.025	0.1400
0.0013	15.9365	3984	0.5750	0.025	0.1411