whisper-synthesized-turkish-2-hour-hlr

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

• Loss: 0.5741
• Wer: 20.5967

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: 0.0001
• 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: 1000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.7454	2.08	100	0.3140	18.8186
0.0822	4.17	200	0.3872	17.8640
0.0577	6.25	300	0.4162	22.8520
0.0552	8.33	400	0.5068	21.3126
0.0638	10.42	500	0.5803	24.4749
0.0571	12.5	600	0.5954	23.7112
0.0351	14.58	700	0.6020	22.5060
0.0159	16.67	800	0.6010	22.9594
0.0088	18.75	900	0.5819	21.6826
0.0012	20.83	1000	0.5741	20.5967

Framework versions

• Transformers 4.28.0
• Pytorch 2.0.0+cu118
• Datasets 2.11.0
• Tokenizers 0.13.3