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End of training

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README.md CHANGED
@@ -6,9 +6,36 @@ tags:
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  - generated_from_trainer
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  datasets:
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  - audiofolder
 
 
 
 
 
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  model-index:
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  - name: distilhubert-finetuned-cry-detector
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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
@@ -17,6 +44,12 @@ should probably proofread and complete it, then remove this comment. -->
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  # distilhubert-finetuned-cry-detector
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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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  ## Model description
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@@ -44,13 +77,22 @@ The following hyperparameters were used during training:
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: cosine
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  - lr_scheduler_warmup_ratio: 0.001
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- - num_epochs: 1
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | No log | 0.9412 | 12 | 0.3379 | 0.9559 | 0.9555 | 0.9564 | 0.9559 |
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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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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+ - f1
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+ - precision
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+ - recall
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  model-index:
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  - name: distilhubert-finetuned-cry-detector
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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: 0.9852941176470589
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+ - name: F1
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+ type: f1
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+ value: 0.9853150765112866
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+ - name: Precision
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+ type: precision
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+ value: 0.9853868369053048
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+ - name: Recall
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+ type: recall
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+ value: 0.9852941176470589
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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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  # distilhubert-finetuned-cry-detector
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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: 0.0332
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+ - Accuracy: 0.9853
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+ - F1: 0.9853
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+ - Precision: 0.9854
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+ - Recall: 0.9853
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  ## Model description
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: cosine
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  - lr_scheduler_warmup_ratio: 0.001
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+ - num_epochs: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | No log | 0.9412 | 12 | 0.1931 | 0.9363 | 0.9365 | 0.9372 | 0.9363 |
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+ | No log | 1.9608 | 25 | 0.0950 | 0.9706 | 0.9704 | 0.9710 | 0.9706 |
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+ | No log | 2.9804 | 38 | 0.0611 | 0.9804 | 0.9804 | 0.9804 | 0.9804 |
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+ | No log | 4.0 | 51 | 0.0492 | 0.9853 | 0.9853 | 0.9853 | 0.9853 |
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+ | No log | 4.9412 | 63 | 0.0588 | 0.9804 | 0.9805 | 0.9814 | 0.9804 |
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+ | No log | 5.9608 | 76 | 0.0368 | 0.9853 | 0.9853 | 0.9854 | 0.9853 |
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+ | No log | 6.9804 | 89 | 0.0382 | 0.9902 | 0.9902 | 0.9903 | 0.9902 |
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+ | No log | 8.0 | 102 | 0.0318 | 0.9951 | 0.9951 | 0.9951 | 0.9951 |
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+ | No log | 8.9412 | 114 | 0.0331 | 0.9853 | 0.9853 | 0.9854 | 0.9853 |
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+ | No log | 9.4118 | 120 | 0.0332 | 0.9853 | 0.9853 | 0.9854 | 0.9853 |
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  ### Framework versions
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