End of training

README.md

@@ -6,24 +6,9 @@ tags:
 - generated_from_trainer
 datasets:
 - marsyas/gtzan
-metrics:
-- accuracy
 model-index:
 - name: distilhubert-finetuned-gtzan
-  results:
-  - task:
-      name: Audio Classification
-      type: audio-classification
-    dataset:
-      name: GTZAN
-      type: marsyas/gtzan
-      config: all
-      split: train
-      args: all
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.82
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,9 +17,6 @@ should probably proofread and complete it, then remove this comment. -->
 # distilhubert-finetuned-gtzan
 
 This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.8674
-- Accuracy: 0.82
 
 ## Model description
 
@@ -63,27 +45,6 @@ The following hyperparameters were used during training:
 - num_epochs: 15
 - mixed_precision_training: Native AMP
 
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.9696        | 1.0   | 150  | 1.9509          | 0.46     |
-| 1.1971        | 2.0   | 300  | 1.2878          | 0.66     |
-| 0.8494        | 3.0   | 450  | 0.9024          | 0.74     |
-| 0.6418        | 4.0   | 600  | 0.8236          | 0.73     |
-| 0.4457        | 5.0   | 750  | 0.5897          | 0.81     |
-| 0.2283        | 6.0   | 900  | 0.5541          | 0.82     |
-| 0.2037        | 7.0   | 1050 | 0.5929          | 0.82     |
-| 0.0992        | 8.0   | 1200 | 0.6360          | 0.83     |
-| 0.0155        | 9.0   | 1350 | 0.7236          | 0.85     |
-| 0.009         | 10.0  | 1500 | 0.7663          | 0.83     |
-| 0.0062        | 11.0  | 1650 | 0.8724          | 0.82     |
-| 0.0044        | 12.0  | 1800 | 0.9651          | 0.83     |
-| 0.004         | 13.0  | 1950 | 0.8713          | 0.83     |
-| 0.004         | 14.0  | 2100 | 0.8965          | 0.83     |
-| 0.0035        | 15.0  | 2250 | 0.8674          | 0.82     |
-
-
 ### Framework versions
 
 - Transformers 4.46.2

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