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Marcos12886
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distilhubert-finetuned-donateacry

Audio Classification
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hubert
Generated from Trainer
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End of training

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Files changed (4) hide show
  1. README.md +6 -5
  2. model.safetensors +1 -1
  3. runs/Sep01_23-37-07_ubumarcos/events.out.tfevents.1725226628.ubumarcos +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -45,7 +45,7 @@ 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 the audiofolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6717
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  - Accuracy: 0.8370
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  - F1: 0.7627
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  - Precision: 0.7005
@@ -77,15 +77,16 @@ 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: 0.03
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- - num_epochs: 3
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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 | 0.8696 | 5 | 1.1779 | 0.7391 | 0.7324 | 0.7336 | 0.7391 |
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- | No log | 1.9130 | 11 | 0.6791 | 0.8370 | 0.7627 | 0.7005 | 0.8370 |
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- | No log | 2.6087 | 15 | 0.6717 | 0.8370 | 0.7627 | 0.7005 | 0.8370 |
 
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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 the audiofolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6654
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  - Accuracy: 0.8370
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  - F1: 0.7627
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  - Precision: 0.7005
 
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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: 0.03
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+ - num_epochs: 8
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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 | 0.8696 | 5 | 0.6723 | 0.8370 | 0.7627 | 0.7005 | 0.8370 |
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+ | No log | 1.9130 | 11 | 0.6778 | 0.8370 | 0.7627 | 0.7005 | 0.8370 |
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+ | No log | 2.9565 | 17 | 0.6690 | 0.8370 | 0.7627 | 0.7005 | 0.8370 |
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+ | No log | 4.0 | 23 | 0.6654 | 0.8370 | 0.7627 | 0.7005 | 0.8370 |
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  ### Framework versions
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