whisper-small-accented-zh-4000steps

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

• Loss: 0.1960
• Wer: 6.1749
• Cer: 2.9133

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: 16
• seed: 42
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• 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	Cer
0.0862	1.6393	1000	0.1556	6.6008	3.0774
0.0072	3.2787	2000	0.1739	6.1835	2.8870
0.0029	4.9180	3000	0.1851	6.1473	2.8853
0.0009	6.5574	4000	0.1960	6.1749	2.9133

Framework versions

• Transformers 4.46.3
• Pytorch 2.4.0
• Datasets 3.1.0
• Tokenizers 0.20.0