bardsai/whisper-medium-pl

Whisper Small PL

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

• Loss: 0.3739
• Wer: 8.5898

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: 32
• eval_batch_size: 16
• 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: 5000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0474	1.1	1000	0.2561	9.4612
0.0119	3.09	2000	0.2901	8.9726
0.0045	5.08	3000	0.3151	8.8870
0.0007	7.07	4000	0.4218	8.6032
0.0005	9.07	5000	0.3739	8.5898

Evaluation results

When tested on diffrent polish ASR datasets (splits: test), this model achieves the following results:

Dataset	WER	WER unnormalized	CER	MER
common_voice_11_0	8.85	21.75	2.63	8.76

Framework versions

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