Hungarians/whisper-tiny-cv16-hu-v2

Whisper Tiny Hu v2

This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 16.0 dataset. It achieves the following results on the evaluation set:

• Loss: 0.1930
• Wer Ortho: 17.3040
• Wer: 15.7367

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: 4e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: constant_with_warmup
• lr_scheduler_warmup_steps: 500
• training_steps: 15000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.5487	0.33	1000	0.5970	55.5492	52.2206
0.3922	0.67	2000	0.4419	43.1109	39.9911
0.3242	1.0	3000	0.3662	37.2727	34.2040
0.2517	1.34	4000	0.3329	33.7890	30.8746
0.2455	1.67	5000	0.2925	30.6185	28.0196
0.1398	2.01	6000	0.2600	27.1709	24.5983
0.1421	2.34	7000	0.2491	26.1291	23.6347
0.1578	2.68	8000	0.2342	24.4761	22.0783
0.0732	3.01	9000	0.2163	22.1245	19.8547
0.0941	3.35	10000	0.2143	22.2058	19.8399
0.0936	3.68	11000	0.2094	20.5980	18.7756
0.0489	4.02	12000	0.2027	18.9630	17.2665
0.0548	4.35	13000	0.1981	18.4933	16.5491
0.0585	4.69	14000	0.1953	17.7195	15.7693
0.0356	5.02	15000	0.1930	17.3040	15.7367

Framework versions

• Transformers 4.36.2
• Pytorch 2.1.0+cu121
• Datasets 2.16.1
• Tokenizers 0.15.0