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End of training

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README.md CHANGED
@@ -4,6 +4,11 @@ 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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  model-index:
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  - name: distilhubert-finetuned-cry-detector
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  results: []
@@ -15,6 +20,12 @@ 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 an unknown dataset.
 
 
 
 
 
 
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  ## Model description
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@@ -42,13 +53,20 @@ 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 | Precision | Recall | F1 |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | No log | 0.9956 | 85 | 0.1412 | 0.9480 | 0.9478 | 0.9480 | 0.9476 |
 
 
 
 
 
 
 
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  ### Framework versions
 
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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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+ metrics:
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+ - accuracy
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+ - precision
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+ - recall
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+ - f1
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  model-index:
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  - name: distilhubert-finetuned-cry-detector
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  results: []
 
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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 an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0878
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+ - Accuracy: 0.9861
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+ - Precision: 0.9861
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+ - Recall: 0.9861
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+ - F1: 0.9861
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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: 8
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | No log | 0.9956 | 85 | 0.1204 | 0.9641 | 0.9641 | 0.9641 | 0.9638 |
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+ | No log | 1.9912 | 170 | 0.0847 | 0.9773 | 0.9772 | 0.9773 | 0.9773 |
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+ | No log | 2.9985 | 256 | 0.1025 | 0.9766 | 0.9769 | 0.9766 | 0.9766 |
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+ | No log | 3.9941 | 341 | 0.0869 | 0.9832 | 0.9835 | 0.9832 | 0.9832 |
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+ | No log | 4.9898 | 426 | 0.0746 | 0.9832 | 0.9834 | 0.9832 | 0.9832 |
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+ | 0.0538 | 5.9971 | 512 | 0.0870 | 0.9861 | 0.9861 | 0.9861 | 0.9861 |
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+ | 0.0538 | 6.9927 | 597 | 0.0890 | 0.9861 | 0.9861 | 0.9861 | 0.9861 |
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+ | 0.0538 | 7.9649 | 680 | 0.0878 | 0.9861 | 0.9861 | 0.9861 | 0.9861 |
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  ### Framework versions
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