---
library_name: transformers
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- audio-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wav2vec-bert-korean-dialect-recognition
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# wav2vec-bert-korean-dialect-recognition

This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/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