Mehtap/base_06

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: 1.9500
• Wer: 2.1895
• Cer: 1.3548

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
1.7116	5.53	100	1.9115	1.1785	0.6901
0.6101	11.11	200	1.5123	1.1039	0.6221
0.2376	16.64	300	1.5636	0.9817	0.6448
0.0591	22.21	400	1.7179	2.2005	1.3384
0.0177	27.75	500	1.8454	1.9205	1.2140
0.0096	33.32	600	1.8529	1.2983	0.7777
0.0048	38.85	700	1.9306	2.3411	1.4385
0.0032	44.43	800	1.9388	1.9523	1.2705
0.0028	49.96	900	1.9472	1.8655	1.2023
0.0026	55.53	1000	1.9500	2.1895	1.3548

Framework versions

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