whisper-synthesized-turkish-2-hour-llr

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: 0.3901
• Wer: 20.1074

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-06
• 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
1.8697	2.08	100	1.5724	43.7232
1.2267	4.17	200	0.8637	90.9905
0.6451	6.25	300	0.6205	85.8473
0.4958	8.33	400	0.5447	93.4368
0.4053	10.42	500	0.4883	52.0644
0.3149	12.5	600	0.4480	32.4821
0.2608	14.58	700	0.4218	24.0334
0.2245	16.67	800	0.4045	22.0764
0.2038	18.75	900	0.3937	19.5227
0.183	20.83	1000	0.3901	20.1074

Framework versions

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