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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: ntu-spml/distilhubert |
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tags: |
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- generated_from_trainer |
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datasets: |
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- boooooook/benben_demo |
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metrics: |
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- accuracy |
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model-index: |
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- name: boooooook/finetuned-bb |
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results: |
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- task: |
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name: Audio Classification |
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type: audio-classification |
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dataset: |
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name: benben_demo |
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type: boooooook/benben_demo |
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config: all |
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split: train |
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args: all |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# boooooook/finetuned-bb |
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This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the benben_demo dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4991 |
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- Accuracy: 0.8 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 10 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 1.8883 | 1.0 | 124 | 1.8304 | 0.5182 | |
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| 1.1287 | 2.0 | 248 | 1.1052 | 0.7 | |
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| 0.897 | 3.0 | 372 | 0.7974 | 0.8182 | |
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| 0.7703 | 4.0 | 496 | 0.6288 | 0.8 | |
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| 0.6084 | 5.0 | 620 | 0.5731 | 0.8364 | |
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| 0.2206 | 6.0 | 744 | 0.5133 | 0.8455 | |
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| 0.1527 | 7.0 | 868 | 0.5248 | 0.8182 | |
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| 0.128 | 8.0 | 992 | 0.4986 | 0.8364 | |
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| 0.1382 | 9.0 | 1116 | 0.4998 | 0.8273 | |
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| 0.0664 | 10.0 | 1240 | 0.4991 | 0.8 | |
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### Framework versions |
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- Transformers 4.51.3 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.1 |
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