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Marcos12886
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distilhubert-finetuned-cry-detector

Audio Classification
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hubert
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End of training

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  1. README.md +12 -9
  2. model.safetensors +1 -1
  3. runs/Sep10_17-49-25_ubumarcos/events.out.tfevents.1725983366.ubumarcos +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -21,9 +21,9 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.0269
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  - Accuracy: 0.9912
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- - Precision: 0.9913
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  - Recall: 0.9912
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  - F1: 0.9912
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@@ -59,13 +59,16 @@ The following hyperparameters were used during training:
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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 | 0.1214 | 0.9582 | 0.9581 | 0.9582 | 0.9581 |
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- | No log | 1.9912 | 170 | 0.0622 | 0.9780 | 0.9781 | 0.9780 | 0.9780 |
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- | No log | 2.9985 | 256 | 0.0362 | 0.9890 | 0.9890 | 0.9890 | 0.9890 |
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- | No log | 3.9941 | 341 | 0.0336 | 0.9927 | 0.9927 | 0.9927 | 0.9927 |
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- | No log | 4.9898 | 426 | 0.0278 | 0.9905 | 0.9905 | 0.9905 | 0.9905 |
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- | 0.0857 | 5.9971 | 512 | 0.0246 | 0.9927 | 0.9927 | 0.9927 | 0.9927 |
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- | 0.0857 | 6.9927 | 597 | 0.0269 | 0.9912 | 0.9913 | 0.9912 | 0.9912 |
 
 
 
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  ### Framework versions
 
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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: 0.0338
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  - Accuracy: 0.9912
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+ - Precision: 0.9912
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  - Recall: 0.9912
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  - F1: 0.9912
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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 | 0.1197 | 0.9538 | 0.9535 | 0.9538 | 0.9536 |
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+ | No log | 1.9912 | 170 | 0.0601 | 0.9832 | 0.9831 | 0.9832 | 0.9831 |
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+ | No log | 2.9985 | 256 | 0.0506 | 0.9868 | 0.9868 | 0.9868 | 0.9868 |
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+ | No log | 3.9941 | 341 | 0.0461 | 0.9861 | 0.9864 | 0.9861 | 0.9862 |
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+ | No log | 4.9898 | 426 | 0.0439 | 0.9890 | 0.9891 | 0.9890 | 0.9890 |
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+ | 0.0779 | 5.9971 | 512 | 0.0396 | 0.9905 | 0.9905 | 0.9905 | 0.9905 |
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+ | 0.0779 | 6.9927 | 597 | 0.0350 | 0.9919 | 0.9919 | 0.9919 | 0.9919 |
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+ | 0.0779 | 8.0 | 683 | 0.0335 | 0.9912 | 0.9912 | 0.9912 | 0.9912 |
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+ | 0.0779 | 8.9956 | 768 | 0.0337 | 0.9912 | 0.9912 | 0.9912 | 0.9912 |
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+ | 0.0779 | 9.9561 | 850 | 0.0338 | 0.9912 | 0.9912 | 0.9912 | 0.9912 |
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  ### Framework versions
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