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---

library_name: transformers
base_model: Kkonjeong/wav2vec2-base-korean
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: audio_cls
  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_cls



This model is a fine-tuned version of [Kkonjeong/wav2vec2-base-korean](https://huggingface.co/Kkonjeong/wav2vec2-base-korean) on an unknown dataset.

It achieves the following results on the evaluation set:

- Loss: 0.4659

- Accuracy: 0.8992



## 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

- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

- mixed_precision_training: Native AMP



### Training results



| Training Loss | Epoch | Step | Validation Loss | Accuracy |

|:-------------:|:-----:|:----:|:---------------:|:--------:|

| 2.6218        | 1.0   | 60   | 2.6014          | 0.1261   |

| 2.2243        | 2.0   | 120  | 2.1842          | 0.2857   |

| 1.7892        | 3.0   | 180  | 1.7467          | 0.5126   |

| 1.0666        | 4.0   | 240  | 1.2378          | 0.7143   |

| 0.8213        | 5.0   | 300  | 0.9638          | 0.7479   |

| 0.4477        | 6.0   | 360  | 0.9652          | 0.7731   |

| 0.2323        | 7.0   | 420  | 0.6221          | 0.8824   |

| 0.1026        | 8.0   | 480  | 0.5741          | 0.8487   |

| 0.0944        | 9.0   | 540  | 0.4625          | 0.8992   |

| 0.057         | 10.0  | 600  | 0.4659          | 0.8992   |





### Framework versions



- Transformers 4.56.0

- Pytorch 2.5.1+cu121

- Datasets 3.6.0

- Tokenizers 0.22.0