audio_cls / README.md
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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: 0.6234
- Accuracy: 0.8571
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.6669 | 1.0 | 30 | 2.6282 | 0.0924 |
| 2.2605 | 2.0 | 60 | 2.2406 | 0.2773 |
| 1.799 | 3.0 | 90 | 1.8493 | 0.4370 |
| 1.2698 | 4.0 | 120 | 1.4725 | 0.7059 |
| 0.8774 | 5.0 | 150 | 1.1926 | 0.7983 |
| 0.6852 | 6.0 | 180 | 0.9671 | 0.7563 |
| 0.4627 | 7.0 | 210 | 0.7951 | 0.8403 |
| 0.3156 | 8.0 | 240 | 0.7054 | 0.8319 |
| 0.1921 | 9.0 | 270 | 0.6380 | 0.8739 |
| 0.1749 | 10.0 | 300 | 0.6234 | 0.8571 |
### Framework versions
- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0