whisper-large-v3-ivn-v1

This model is a fine-tuned version of openai/whisper-large-v3 on the audiofolder dataset. It achieves the following results on the evaluation set:

• Loss: 1.8302
• Wer: 70.5679

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
0.0274	14.29	1000	1.4520	78.4974
0.0033	28.57	2000	1.6206	73.4296
0.0004	42.86	3000	1.7704	70.3553
0.0002	57.14	4000	1.8302	70.5679

Framework versions

• Transformers 4.37.1
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.1