julie200/whisper-small-mi_nz

Whisper Small Maori

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

• Loss: 0.7756
• Wer: 30.4816

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: 64
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 100
• training_steps: 500
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2693	7.02	100	0.6741	35.4845
0.0084	15.01	200	0.7756	30.4816
0.0029	23.0	300	0.8154	31.4744
0.002	30.02	400	0.8320	31.3777
0.0017	38.01	500	0.8372	31.5163

Framework versions

• Transformers 4.26.0.dev0
• Pytorch 1.13.1+cu117
• Datasets 2.8.1.dev0
• Tokenizers 0.13.2