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---
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
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