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---
library_name: transformers
base_model: Kkonjeong/wav2vec2-base-korean
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: kws
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. -->
# kws
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: 0.4170
- Accuracy: 0.9474
## 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: 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: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 2 | 1.8732 | 0.3158 |
| No log | 2.0 | 4 | 1.9113 | 0.2105 |
| No log | 3.0 | 6 | 1.7446 | 0.4737 |
| No log | 4.0 | 8 | 1.6420 | 0.7895 |
| No log | 5.0 | 10 | 1.5209 | 0.6842 |
| No log | 6.0 | 12 | 1.4078 | 0.6842 |
| No log | 7.0 | 14 | 1.3386 | 0.7895 |
| No log | 8.0 | 16 | 1.2170 | 0.7895 |
| No log | 9.0 | 18 | 1.1401 | 0.9474 |
| No log | 10.0 | 20 | 1.0615 | 0.8947 |
| No log | 11.0 | 22 | 1.0216 | 0.8947 |
| No log | 12.0 | 24 | 1.0372 | 0.7895 |
| No log | 13.0 | 26 | 0.9032 | 0.9474 |
| No log | 14.0 | 28 | 0.8303 | 0.9474 |
| No log | 15.0 | 30 | 0.7810 | 0.9474 |
| No log | 16.0 | 32 | 0.7487 | 0.9474 |
| No log | 17.0 | 34 | 0.6966 | 0.9474 |
| No log | 18.0 | 36 | 0.6569 | 0.9474 |
| No log | 19.0 | 38 | 0.6278 | 0.9474 |
| No log | 20.0 | 40 | 0.5570 | 0.9474 |
| No log | 21.0 | 42 | 0.5196 | 0.9474 |
| No log | 22.0 | 44 | 0.5068 | 0.9474 |
| No log | 23.0 | 46 | 0.5700 | 0.9474 |
| No log | 24.0 | 48 | 0.5661 | 0.9474 |
| No log | 25.0 | 50 | 0.5427 | 0.9474 |
| No log | 26.0 | 52 | 0.4936 | 0.9474 |
| No log | 27.0 | 54 | 0.4339 | 0.9474 |
| No log | 28.0 | 56 | 0.4257 | 0.9474 |
| No log | 29.0 | 58 | 0.4186 | 0.9474 |
| No log | 30.0 | 60 | 0.4170 | 0.9474 |
### Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
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