---
library_name: transformers
base_model: Kkonjeong/wav2vec2-base-korean
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: audio_cls2
  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. -->

# audio_cls2

This model is a fine-tuned version of [Kkonjeong/wav2vec2-base-korean](https://huggingface.co/Kkonjeong/wav2vec2-base-korean) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9947
- Accuracy: 0.1538

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 2    | 1.9488          | 0.4615   |
| No log        | 2.0   | 4    | 1.9549          | 0.0769   |
| No log        | 3.0   | 6    | 1.9348          | 0.1538   |
| No log        | 4.0   | 8    | 1.9568          | 0.1538   |
| No log        | 5.0   | 10   | 1.9823          | 0.0      |
| No log        | 6.0   | 12   | 1.9865          | 0.1538   |
| No log        | 7.0   | 14   | 1.9931          | 0.1538   |
| No log        | 8.0   | 16   | 1.9951          | 0.1538   |
| No log        | 9.0   | 18   | 1.9933          | 0.1538   |
| No log        | 10.0  | 20   | 1.9947          | 0.1538   |


### Framework versions

- Transformers 5.10.2
- Pytorch 2.12.0+cu130
- Datasets 4.8.5
- Tokenizers 0.22.2