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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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Files changed (4) hide show
  1. README.md +10 -7
  2. model.safetensors +1 -1
  3. runs/Aug07_17-25-05_DesMar/events.out.tfevents.1723044305.DesMar.24280.0 +3 -0
  4. training_args.bin +1 -1
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: 0.7191011235955056
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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: 1.1308
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- - Accuracy: 0.7191
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  ## Model description
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@@ -60,15 +60,18 @@ 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: cosine
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- - num_epochs: 3
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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 | 1.4269 | 0.5674 |
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- | No log | 1.9775 | 22 | 1.1754 | 0.7022 |
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- | No log | 2.9663 | 33 | 1.1308 | 0.7191 |
 
 
 
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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: 0.8595505617977528
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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: 0.7516
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+ - Accuracy: 0.8596
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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: cosine
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+ - num_epochs: 6
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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 | 1.4029 | 0.5843 |
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+ | No log | 1.9775 | 22 | 1.0708 | 0.7022 |
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+ | No log | 2.9663 | 33 | 0.9015 | 0.8090 |
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+ | No log | 3.9551 | 44 | 0.8003 | 0.8427 |
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+ | No log | 4.9438 | 55 | 0.7582 | 0.8483 |
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+ | No log | 5.9326 | 66 | 0.7516 | 0.8596 |
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  ### Framework versions
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