Whisper-Tiny-german-HanNeurAI

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

• Loss: 0.5505
• Wer: 31.4346

This model is part of my school project, it uses shuffled 100k rows of train dataset since the computation power is limited.

Additional information can be found in this github: HanCreation/Whisper-Tiny-German

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
0.4824	0.16	1000	0.6305	35.5019
0.4284	0.32	2000	0.5855	33.3615
0.4152	0.48	3000	0.5610	32.1068
0.4387	0.64	4000	0.5505	31.4346

Framework versions

• Transformers 4.40.2
• Pytorch 2.3.0
• Datasets 2.19.1
• Tokenizers 0.19.1

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure