bardsai/whisper-medium-pl-v2

Whisper Medium PL

This model is a fine-tuned version of openai/whisper-medium on the Common Voice 11.0 and the FLEURS datasets. It achieves the following results on the evaluation set:

• Loss: 0.3947
• Wer: 8.6872

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: 4
• eval_batch_size: 1
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• training_steps: 8000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0805	0.48	500	0.2556	10.4888
0.0685	0.96	1000	0.2462	10.7608
0.0356	1.45	1500	0.2561	9.6728
0.0337	1.93	2000	0.2327	9.6459
0.017	2.41	2500	0.2444	9.9464
0.0179	2.9	3000	0.2554	9.6476
0.0056	3.38	3500	0.3001	9.3638
0.007	3.86	4000	0.2809	9.2245
0.0033	4.34	4500	0.3235	9.3437
0.0024	4.83	5000	0.3148	9.0633
0.0008	5.31	5500	0.3416	9.0112
0.0011	5.79	6000	0.3876	9.1858
0.0004	6.27	6500	0.3745	8.7292
0.0003	6.76	7000	0.3704	9.0314
0.0003	7.24	7500	0.3929	8.6553
0.0002	7.72	8000	0.3947	8.6872

Framework versions

• Transformers 4.26.0.dev0
• Pytorch 1.13.0+cu117
• Datasets 2.7.1.dev0
• Tokenizers 0.13.2