fimster/whisper-small-sv-SE-NST

Whisper Small sv-SE NST - Lab 2

This model is a fine-tuned version of openai/whisper-small on the NST Swedish ASR dataset. It achieves the following results on the evaluation set:

• Loss: 0.1305
• Wer: 10.1678

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: 8
• 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: 4000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1635	0.67	1000	0.1694	13.4993
0.07	1.33	2000	0.1431	11.3802
0.0597	2.0	3000	0.1302	10.4682
0.0193	2.67	4000	0.1305	10.1678

Framework versions

• Transformers 4.26.0.dev0
• Pytorch 1.13.0+cu116
• Datasets 2.7.1
• Tokenizers 0.13.2