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cogniveon/eeem069_heart_murmur_classification

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README.md CHANGED
@@ -5,9 +5,24 @@ tags:
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  - generated_from_trainer
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  datasets:
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  - arrow
 
 
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  model-index:
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  - name: eeem069_heart_murmur_classification
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- results: []
 
 
 
 
 
 
 
 
 
 
 
 
 
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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
@@ -16,6 +31,9 @@ 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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  ## Model description
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@@ -35,15 +53,40 @@ More information needed
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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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  - 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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  ### Framework versions
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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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  # 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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  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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+
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+ ### Training results
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+
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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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+
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  ### Framework versions
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