HERIUN/wav2vec-bert-korean-dialect-recognition_v1

Do not use this model. use https://huggingface.co/HERIUN/wav2vec-bert-korean-dialect-recognition

It is trained mini dataset. also evaluation.

wav2vec-bert-korean-dialect-recognition

This model is a fine-tuned version of facebook/w2v-bert-2.0 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.6935
• Accuracy: 0.7453

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: 5e-05
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Use OptimizerNames.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
• num_epochs: 10
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.1772	1.0	32734	0.9692	0.6393
1.1915	2.0	65468	0.8570	0.6765
1.198	3.0	98202	0.7810	0.7097
1.2072	4.0	130936	0.7748	0.7121
1.2897	5.0	163670	0.7394	0.7252
1.206	6.0	196404	0.7457	0.7196
1.0204	7.0	229138	0.7299	0.7273
1.1207	8.0	261872	0.7225	0.7330
1.3417	9.0	294606	0.6936	0.7450
1.1021	10.0	327340	0.7014	0.7415

Framework versions

• Transformers 4.47.1
• Pytorch 2.5.1+cu124
• Datasets 3.2.0
• Tokenizers 0.21.0