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--- |
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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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- audiofolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: DH_ONM_WORDS |
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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: audiofolder |
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type: audiofolder |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.999762962962963 |
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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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# DH_ONM_WORDS |
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This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the audiofolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0021 |
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- Accuracy: 0.9998 |
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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: 3e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- distributed_type: tpu |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 5 |
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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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| 0.0251 | 1.0 | 263 | 0.0150 | 0.9993 | |
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| 0.0085 | 2.0 | 527 | 0.0045 | 0.9997 | |
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| 0.0026 | 3.0 | 791 | 0.0029 | 0.9998 | |
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| 0.0018 | 4.0 | 1055 | 0.0023 | 0.9998 | |
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| 0.0019 | 4.99 | 1315 | 0.0021 | 0.9998 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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