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--- |
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license: apache-2.0 |
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base_model: juniorjukeko/audio-class-minds14 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- minds14 |
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metrics: |
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- accuracy |
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model-index: |
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- name: audio-class-minds14 |
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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: minds14 |
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type: minds14 |
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config: en-US |
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split: train |
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args: en-US |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.08849557522123894 |
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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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# audio-class-minds14 |
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This model is a fine-tuned version of [juniorjukeko/audio-class-minds14](https://huggingface.co/juniorjukeko/audio-class-minds14) on the minds14 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.6380 |
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- Accuracy: 0.0885 |
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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: 0.0005 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 143 |
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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: 10 |
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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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| No log | 0.8 | 3 | 2.6452 | 0.0796 | |
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| No log | 1.87 | 7 | 2.6469 | 0.0796 | |
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| 2.643 | 2.93 | 11 | 2.6449 | 0.0708 | |
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| 2.643 | 4.0 | 15 | 2.6426 | 0.0708 | |
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| 2.643 | 4.8 | 18 | 2.6429 | 0.0708 | |
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| 2.649 | 5.87 | 22 | 2.6413 | 0.0885 | |
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| 2.649 | 6.93 | 26 | 2.6388 | 0.0885 | |
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| 2.6382 | 8.0 | 30 | 2.6380 | 0.0885 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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