This model is a fine-tuned version of Kkonjeong/wav2vec2-base-korean on the None dataset. It achieves the following results on the evaluation set: Loss: 0.2259 Accuracy: 1.0
Fuente del modelo
Descripción de la fuente
This model is a fine-tuned version of Kkonjeong/wav2vec2-base-korean on the None dataset. It achieves the following results on the evaluation set:
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Fuentes
1 fuenteVerificado 13 sept
Artefactos del modelo
1 artefactoExtractos de fuentes
2 extractosMore information needed
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 2 | 1.9212 | 0.2632 |
| No log | 2.0 | 4 | 1.8581 | 0.2105 |
| No log | 3.0 | 6 | 1.6924 | 0.5263 |
| No log | 4.0 | 8 | 1.5170 | 0.5789 |
| No log | 5.0 | 10 | 1.3486 | 0.8421 |
--- library_name: transformers base_model: Kkonjeong/wav2vec2-base-korean tags: - generated_from_trainer metrics: - accuracy model-index: - name: korean_kws2 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. --> # korean_kws2 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: 0.2259 - Accuracy: 1.0 ## 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 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 2 | 1.9212 | 0.2632 | | No log | 2.0 | 4 | 1.8581 | 0.2105 | | No log | 3.0 | 6 | 1.6924 | 0.5263 | | No log | 4.0 | 8 | 1.5170 | 0.5789 | | No log | 5.0 | 10 | 1.3486 | 0.8421 | | No log | 6.0 | 12 | 1.1842 | 1.0 | | No log | 7.0 | 14 | 1.0589 | 0.9474 | | No log | 8.0 | 16 | 0.9919 | 0.8947 | | No log | 9.0 | 18 | 0.7978 | 1.0 | | No log | 10.0 | 20 | 0.7261 | 1.0 | | No log | 11.0 | 22 | 0.6440 | 1.0 | | No log | 12.0 | 24 | 0.6020 | 1.0 | | No log | 13.0 | 26 | 0.5278 | 1.0 | | No log | 14.0 | 28 | 0.4831 | 1.0 | | No log | 15.0 | 30 | 0.4255 | 1.0 | | No log | 16.0 | 32 | 0.3844 | 1.0 | | No log | 17.0 | 34 | 0.3504 | 1.0 | | No log | 18.0 | 36 | 0.3277 | 1.0 | | No log | 19.0 | 38 | 0.3066 | 1.0 | | No log | 20.0 | 40 | 0.2919 | 1.0 | | No log | 21.0 | 42 | 0.2793 | 1.0 | | No log | 22.0 | 44 | 0.2668 | 1.0 | | No log | 23.0 | 46 | 0.2562 | 1.0 | | No log | 24.0 | 48 | 0.2479 | 1.0 | | No log | 25.0 | 50 | 0.2410 | 1.0 | | No log | 26.0 | 52 | 0.2355 | 1.0 | | No log | 27.0 | 54 | 0.2313 | 1.0 |...
Source context: 2 downloads · 0 likes · Pipeline audio-classification · Library transformers · Repo devtaco/korean_kws2
| No log | 6.0 | 12 | 1.1842 | 1.0 |
| No log | 7.0 | 14 | 1.0589 | 0.9474 |
| No log | 8.0 | 16 | 0.9919 | 0.8947 |
| No log | 9.0 | 18 | 0.7978 | 1.0 |
| No log | 10.0 | 20 | 0.7261 | 1.0 |
| No log | 11.0 | 22 | 0.6440 | 1.0 |
| No log | 12.0 | 24 | 0.6020 | 1.0 |
| No log | 13.0 | 26 | 0.5278 | 1.0 |
| No log | 14.0 | 28 | 0.4831 | 1.0 |
| No log | 15.0 | 30 | 0.4255 | 1.0 |
| No log | 16.0 | 32 | 0.3844 | 1.0 |
| No log | 17.0 | 34 | 0.3504 | 1.0 |
| No log | 18.0 | 36 | 0.3277 | 1.0 |
| No log | 19.0 | 38 | 0.3066 | 1.0 |
| No log | 20.0 | 40 | 0.2919 | 1.0 |
| No log | 21.0 | 42 | 0.2793 | 1.0 |
| No log | 22.0 | 44 | 0.2668 | 1.0 |
| No log | 23.0 | 46 | 0.2562 | 1.0 |
| No log | 24.0 | 48 | 0.2479 | 1.0 |
| No log | 25.0 | 50 | 0.2410 | 1.0 |
| No log | 26.0 | 52 | 0.2355 | 1.0 |
| No log | 27.0 | 54 | 0.2313 | 1.0 |
| No log | 28.0 | 56 | 0.2283 | 1.0 |
| No log | 29.0 | 58 | 0.2267 | 1.0 |
| No log | 30.0 | 60 | 0.2259 | 1.0 |