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distilhubert-finetuned-babycry-v7

Audio Classification
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hubert
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  1. README.md +15 -15
  2. runs/Oct02_17-13-51_315dc4c4c032/events.out.tfevents.1727889530.315dc4c4c032.673.2 +3 -0
README.md CHANGED
@@ -21,7 +21,7 @@ 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: 0.5860
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  - Accuracy: {'accuracy': 0.8695652173913043}
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  - F1: 0.8089
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  - Precision: 0.7561
@@ -59,20 +59,20 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:------:|:----:|:---------------:|:--------------------------------:|:------:|:---------:|:------:|
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- | 1.005 | 0.5435 | 25 | 0.6526 | {'accuracy': 0.8695652173913043} | 0.8089 | 0.7561 | 0.8696 |
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- | 0.7736 | 1.0870 | 50 | 0.6396 | {'accuracy': 0.8695652173913043} | 0.8089 | 0.7561 | 0.8696 |
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- | 0.5618 | 1.6304 | 75 | 0.6990 | {'accuracy': 0.8695652173913043} | 0.8089 | 0.7561 | 0.8696 |
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- | 0.8623 | 2.1739 | 100 | 0.5802 | {'accuracy': 0.8695652173913043} | 0.8089 | 0.7561 | 0.8696 |
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- | 0.6532 | 2.7174 | 125 | 0.6205 | {'accuracy': 0.8695652173913043} | 0.8089 | 0.7561 | 0.8696 |
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- | 0.8076 | 3.2609 | 150 | 0.6168 | {'accuracy': 0.8695652173913043} | 0.8089 | 0.7561 | 0.8696 |
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- | 0.7581 | 3.8043 | 175 | 0.5917 | {'accuracy': 0.8695652173913043} | 0.8089 | 0.7561 | 0.8696 |
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- | 0.7525 | 4.3478 | 200 | 0.5988 | {'accuracy': 0.8695652173913043} | 0.8089 | 0.7561 | 0.8696 |
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- | 0.6566 | 4.8913 | 225 | 0.5997 | {'accuracy': 0.8695652173913043} | 0.8089 | 0.7561 | 0.8696 |
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- | 0.6845 | 5.4348 | 250 | 0.5815 | {'accuracy': 0.8695652173913043} | 0.8089 | 0.7561 | 0.8696 |
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- | 0.6812 | 5.9783 | 275 | 0.5830 | {'accuracy': 0.8695652173913043} | 0.8089 | 0.7561 | 0.8696 |
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- | 0.6548 | 6.5217 | 300 | 0.5855 | {'accuracy': 0.8695652173913043} | 0.8089 | 0.7561 | 0.8696 |
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- | 0.6555 | 7.0652 | 325 | 0.5859 | {'accuracy': 0.8695652173913043} | 0.8089 | 0.7561 | 0.8696 |
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- | 0.7294 | 7.6087 | 350 | 0.5861 | {'accuracy': 0.8695652173913043} | 0.8089 | 0.7561 | 0.8696 |
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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: 0.5864
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  - Accuracy: {'accuracy': 0.8695652173913043}
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  - F1: 0.8089
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  - Precision: 0.7561
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:------:|:----:|:---------------:|:--------------------------------:|:------:|:---------:|:------:|
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+ | 0.7417 | 0.5435 | 25 | 0.5925 | {'accuracy': 0.8695652173913043} | 0.8089 | 0.7561 | 0.8696 |
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+ | 0.7226 | 1.0870 | 50 | 0.6167 | {'accuracy': 0.8695652173913043} | 0.8089 | 0.7561 | 0.8696 |
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+ | 0.5606 | 1.6304 | 75 | 0.6808 | {'accuracy': 0.8695652173913043} | 0.8089 | 0.7561 | 0.8696 |
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+ | 0.8858 | 2.1739 | 100 | 0.5850 | {'accuracy': 0.8695652173913043} | 0.8089 | 0.7561 | 0.8696 |
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+ | 0.6573 | 2.7174 | 125 | 0.5968 | {'accuracy': 0.8695652173913043} | 0.8089 | 0.7561 | 0.8696 |
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+ | 0.7942 | 3.2609 | 150 | 0.6142 | {'accuracy': 0.8695652173913043} | 0.8089 | 0.7561 | 0.8696 |
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+ | 0.7497 | 3.8043 | 175 | 0.5915 | {'accuracy': 0.8695652173913043} | 0.8089 | 0.7561 | 0.8696 |
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+ | 0.7408 | 4.3478 | 200 | 0.5899 | {'accuracy': 0.8695652173913043} | 0.8089 | 0.7561 | 0.8696 |
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+ | 0.6499 | 4.8913 | 225 | 0.5989 | {'accuracy': 0.8695652173913043} | 0.8089 | 0.7561 | 0.8696 |
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+ | 0.6725 | 5.4348 | 250 | 0.5865 | {'accuracy': 0.8695652173913043} | 0.8089 | 0.7561 | 0.8696 |
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+ | 0.6797 | 5.9783 | 275 | 0.5852 | {'accuracy': 0.8695652173913043} | 0.8089 | 0.7561 | 0.8696 |
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+ | 0.6553 | 6.5217 | 300 | 0.5861 | {'accuracy': 0.8695652173913043} | 0.8089 | 0.7561 | 0.8696 |
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+ | 0.6535 | 7.0652 | 325 | 0.5863 | {'accuracy': 0.8695652173913043} | 0.8089 | 0.7561 | 0.8696 |
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+ | 0.7297 | 7.6087 | 350 | 0.5865 | {'accuracy': 0.8695652173913043} | 0.8089 | 0.7561 | 0.8696 |
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  ### Framework versions
runs/Oct02_17-13-51_315dc4c4c032/events.out.tfevents.1727889530.315dc4c4c032.673.2 ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:634479a3fb781c0e679eb465bd74f03acf527908f49d0d94f50751607a7872dd
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+ size 508