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End of training

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README.md CHANGED
@@ -6,9 +6,36 @@ tags:
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  - generated_from_trainer
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  datasets:
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  - audiofolder
 
 
 
 
 
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  model-index:
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  - name: distilhubert-finetuned-mixed-data
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- results: []
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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
@@ -17,6 +44,12 @@ should probably proofread and complete it, then remove this comment. -->
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  # distilhubert-finetuned-mixed-data
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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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  ## Model description
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@@ -44,13 +77,22 @@ 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: 0.001
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- - num_epochs: 1
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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 | 0.9664 | 18 | 0.9747 | 0.7282 | 0.6705 | 0.6223 | 0.7282 |
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  - generated_from_trainer
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  datasets:
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  - audiofolder
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+ metrics:
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+ - accuracy
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+ - f1
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+ - precision
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+ - recall
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  model-index:
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  - name: distilhubert-finetuned-mixed-data
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+ results:
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+ - task:
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+ name: Audio Classification
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+ type: audio-classification
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+ dataset:
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+ name: audiofolder
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+ type: audiofolder
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+ config: default
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+ split: None
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.889261744966443
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+ - name: F1
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+ type: f1
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+ value: 0.8885260378939167
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+ - name: Precision
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+ type: precision
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+ value: 0.887959005693052
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+ - name: Recall
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+ type: recall
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+ value: 0.889261744966443
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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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  # distilhubert-finetuned-mixed-data
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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: 0.3033
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+ - Accuracy: 0.8893
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+ - F1: 0.8885
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+ - Precision: 0.8880
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+ - Recall: 0.8893
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  ## Model description
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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: 0.001
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+ - num_epochs: 10
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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 | 0.9664 | 18 | 0.6703 | 0.7819 | 0.7264 | 0.6898 | 0.7819 |
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+ | No log | 1.9866 | 37 | 0.5053 | 0.7752 | 0.7203 | 0.6849 | 0.7752 |
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+ | No log | 2.9530 | 55 | 0.4473 | 0.7987 | 0.7457 | 0.7193 | 0.7987 |
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+ | No log | 3.9732 | 74 | 0.3820 | 0.8691 | 0.8578 | 0.8854 | 0.8691 |
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+ | No log | 4.9933 | 93 | 0.3435 | 0.8691 | 0.8671 | 0.8704 | 0.8691 |
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+ | No log | 5.9597 | 111 | 0.3176 | 0.8859 | 0.8855 | 0.8868 | 0.8859 |
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+ | No log | 6.9799 | 130 | 0.3045 | 0.8859 | 0.8853 | 0.8850 | 0.8859 |
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+ | No log | 8.0 | 149 | 0.3051 | 0.8859 | 0.8849 | 0.8843 | 0.8859 |
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+ | No log | 8.9664 | 167 | 0.3031 | 0.8926 | 0.8913 | 0.8910 | 0.8926 |
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+ | No log | 9.6644 | 180 | 0.3033 | 0.8893 | 0.8885 | 0.8880 | 0.8893 |
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  ### Framework versions
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