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---
library_name: transformers
base_model: fleek/wav2vec-large-xlsr-korean
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wav2vec2-xlsr-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. -->
# wav2vec2-xlsr-korean-dialect-recognition
This model is a fine-tuned version of [fleek/wav2vec-large-xlsr-korean](https://huggingface.co/fleek/wav2vec-large-xlsr-korean) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5291
- Accuracy: 0.8063
## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 2.8542 | 0.0681 | 100 | 1.4936 | 0.3803 |
| 1.9555 | 0.1362 | 200 | 1.1916 | 0.5237 |
| 2.3132 | 0.2043 | 300 | 0.9826 | 0.6180 |
| 1.8724 | 0.2724 | 400 | 0.9512 | 0.6411 |
| 1.9331 | 0.3405 | 500 | 0.8138 | 0.6857 |
| 1.6761 | 0.4086 | 600 | 0.7749 | 0.6932 |
| 1.7902 | 0.4767 | 700 | 0.7694 | 0.7028 |
| 1.9041 | 0.5448 | 800 | 0.7199 | 0.7194 |
| 1.8659 | 0.6129 | 900 | 0.7010 | 0.7382 |
| 1.9123 | 0.6810 | 1000 | 0.6067 | 0.7753 |
| 1.2564 | 0.7491 | 1100 | 0.6073 | 0.7726 |
| 0.8368 | 0.8172 | 1200 | 0.6203 | 0.7729 |
| 1.1841 | 0.8853 | 1300 | 0.5312 | 0.7988 |
| 1.0372 | 0.9534 | 1400 | 0.5291 | 0.8063 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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