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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- arrow |
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metrics: |
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- accuracy |
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model-index: |
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- name: eeem069_heart_murmur_classification |
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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: arrow |
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type: arrow |
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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: 0.8221153846153846 |
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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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# eeem069_heart_murmur_classification |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the arrow dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5614 |
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- Accuracy: 0.8221 |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 256 |
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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: 20 |
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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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| 1.0582 | 0.92 | 9 | 0.8806 | 0.8045 | |
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| 0.804 | 1.95 | 19 | 0.6482 | 0.8045 | |
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| 0.6425 | 2.97 | 29 | 0.6061 | 0.8045 | |
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| 0.6025 | 4.0 | 39 | 0.5924 | 0.8045 | |
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| 0.5865 | 4.92 | 48 | 0.5879 | 0.8045 | |
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| 0.6228 | 5.95 | 58 | 0.5834 | 0.8045 | |
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| 0.5676 | 6.97 | 68 | 0.5840 | 0.8045 | |
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| 0.5856 | 8.0 | 78 | 0.5890 | 0.8045 | |
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| 0.5946 | 8.92 | 87 | 0.5785 | 0.8045 | |
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| 0.586 | 9.95 | 97 | 0.5726 | 0.8045 | |
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| 0.5846 | 10.97 | 107 | 0.5723 | 0.8045 | |
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| 0.5545 | 12.0 | 117 | 0.5707 | 0.8237 | |
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| 0.5569 | 12.92 | 126 | 0.5846 | 0.8141 | |
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| 0.5997 | 13.95 | 136 | 0.5649 | 0.8173 | |
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| 0.5404 | 14.97 | 146 | 0.5625 | 0.8221 | |
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| 0.5438 | 16.0 | 156 | 0.5641 | 0.8189 | |
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| 0.5294 | 16.92 | 165 | 0.5633 | 0.8221 | |
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| 0.5196 | 17.95 | 175 | 0.5613 | 0.8205 | |
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| 0.5369 | 18.46 | 180 | 0.5614 | 0.8221 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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