End of training

README.md

@@ -1,24 +1,13 @@
 ---
 license: apache-2.0
+base_model: ntu-spml/distilhubert
 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
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.65
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -26,10 +15,7 @@ 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 None dataset.
-It achieves the following results on the evaluation set:
-- Loss: 1.4484
-- Accuracy: 0.65
+This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
 
 ## Model description
 
@@ -48,30 +34,16 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 1e-05
+- learning_rate: 0.0001
 - train_batch_size: 8
 - eval_batch_size: 8
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 8
+- num_epochs: 1
 - mixed_precision_training: Native AMP
 
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 2.2604        | 1.0   | 113  | 2.2157          | 0.38     |
-| 1.972         | 2.0   | 226  | 1.9740          | 0.45     |
-| 1.8073        | 3.0   | 339  | 1.7988          | 0.54     |
-| 1.6946        | 4.0   | 452  | 1.6666          | 0.64     |
-| 1.582         | 5.0   | 565  | 1.5732          | 0.61     |
-| 1.6468        | 6.0   | 678  | 1.4905          | 0.65     |
-| 1.4905        | 7.0   | 791  | 1.4661          | 0.65     |
-| 1.4801        | 8.0   | 904  | 1.4484          | 0.65     |
-
-
 ### Framework versions
 
 - Transformers 4.35.2

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