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distilhubert-finetuned-donateacry

Audio Classification
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hubert
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  1. README.md +7 -31
  2. runs/Jul03_19-30-28_DesMar/events.out.tfevents.1720027903.DesMar.15508.1 +3 -0
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.8932584269662921
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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
@@ -32,8 +32,8 @@ 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: 0.5034
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- - Accuracy: 0.8933
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  ## Model description
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@@ -60,37 +60,13 @@ The following hyperparameters were used during training:
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  - total_train_batch_size: 64
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 25
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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- |:-------------:|:-------:|:----:|:---------------:|:--------:|
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- | No log | 0.9888 | 11 | 0.9525 | 0.7303 |
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- | No log | 1.9775 | 22 | 1.2765 | 0.5393 |
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- | No log | 2.9663 | 33 | 0.6634 | 0.7978 |
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- | No log | 3.9551 | 44 | 0.6369 | 0.8202 |
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- | No log | 4.9438 | 55 | 0.5328 | 0.8596 |
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- | No log | 5.9326 | 66 | 0.5146 | 0.8652 |
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- | No log | 6.9213 | 77 | 0.5200 | 0.8764 |
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- | No log | 8.0 | 89 | 0.5213 | 0.8708 |
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- | No log | 8.9888 | 100 | 0.6062 | 0.8596 |
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- | No log | 9.9775 | 111 | 0.5938 | 0.8652 |
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- | No log | 10.9663 | 122 | 0.5247 | 0.8652 |
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- | No log | 11.9551 | 133 | 0.7004 | 0.8483 |
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- | No log | 12.9438 | 144 | 0.5388 | 0.8876 |
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- | No log | 13.9326 | 155 | 0.4856 | 0.8876 |
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- | No log | 14.9213 | 166 | 0.5380 | 0.8764 |
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- | No log | 16.0 | 178 | 0.5055 | 0.8876 |
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- | No log | 16.9888 | 189 | 0.5217 | 0.8876 |
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- | No log | 17.9775 | 200 | 0.5034 | 0.8933 |
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- | No log | 18.9663 | 211 | 0.4745 | 0.8876 |
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- | No log | 19.9551 | 222 | 0.4812 | 0.8876 |
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- | No log | 20.9438 | 233 | 0.4709 | 0.8820 |
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- | No log | 21.9326 | 244 | 0.4824 | 0.8876 |
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- | No log | 22.9213 | 255 | 0.4819 | 0.8876 |
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- | No log | 24.0 | 267 | 0.4877 | 0.8933 |
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- | No log | 24.7191 | 275 | 0.4866 | 0.8933 |
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.6966292134831461
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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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  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: 0.9121
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+ - Accuracy: 0.6966
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  ## Model description
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  - total_train_batch_size: 64
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 1
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | No log | 0.9888 | 11 | 0.9121 | 0.6966 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
runs/Jul03_19-30-28_DesMar/events.out.tfevents.1720027903.DesMar.15508.1 ADDED
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