Mehtap/base_07

base Turkish Whisper (bTW)

This model is a fine-tuned version of openai/whisper-base on the Ermetal Meetings dataset. It achieves the following results on the evaluation set:

• Loss: 1.1836
• Wer: 1.7109
• Cer: 1.2860

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: 16
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 4
• 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: 500
• training_steps: 1000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
1.7878	4.74	100	1.4516	0.8560	0.5525
0.6701	9.51	200	0.9194	0.8543	0.6112
0.3364	14.28	300	0.8871	0.7415	0.4992
0.1228	19.05	400	0.9671	0.9052	0.6678
0.0355	23.78	500	1.0515	0.8961	0.6208
0.0148	28.55	600	1.0684	0.6644	0.3694
0.0056	33.32	700	1.1488	1.3315	0.8732
0.0041	38.09	800	1.1700	1.7415	1.1934
0.0034	42.83	900	1.1801	1.7745	1.2643
0.0032	47.6	1000	1.1836	1.7109	1.2860

Framework versions

• Transformers 4.26.0
• Pytorch 1.12.0+cu102
• Datasets 2.9.0
• Tokenizers 0.13.2