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distilhubert-finetuned-gtzan

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 +6 -6
  2. model.safetensors +1 -1
  3. runs/Dec24_19-24-48_e2ac1b75f3e9/events.out.tfevents.1703445889.e2ac1b75f3e9.529.2 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -8,7 +8,7 @@ datasets:
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  metrics:
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  - accuracy
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  model-index:
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- - name: distilhubert
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  results:
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  - task:
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  name: Audio Classification
@@ -18,7 +18,7 @@ model-index:
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  type: marsyas/gtzan
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  config: all
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  split: train
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- args: 'config: "all"'
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  metrics:
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  - name: Accuracy
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  type: accuracy
@@ -28,11 +28,11 @@ model-index:
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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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  should probably proofread and complete it, then remove this comment. -->
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- # distilhubert
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  This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.8461
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  - Accuracy: 0.53
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  ## Model description
@@ -52,7 +52,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 5e-05
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
@@ -66,7 +66,7 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 1.9351 | 1.0 | 113 | 1.8461 | 0.53 |
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  ### Framework versions
 
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  metrics:
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  - accuracy
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  model-index:
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+ - name: distilhubert-finetuned-gtzan
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  results:
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  - task:
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  name: Audio Classification
 
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  type: marsyas/gtzan
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  config: all
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  split: train
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+ args: all
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  metrics:
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  - name: Accuracy
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  type: accuracy
 
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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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  should probably proofread and complete it, then remove this comment. -->
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+ # distilhubert-finetuned-gtzan
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  This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.5669
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  - Accuracy: 0.53
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  ## Model description
 
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.6652 | 1.0 | 113 | 1.5669 | 0.53 |
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  ### Framework versions
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