End of training

README.md

@@ -1,7 +1,7 @@
 ---
 library_name: transformers
 license: apache-2.0
-base_model: ntu-spml/distilhubert
+base_model: MariaK/distilhubert-finetuned-gtzan-v2
 tags:
 - generated_from_trainer
 datasets:
@@ -9,7 +9,7 @@ datasets:
 metrics:
 - accuracy
 model-index:
-- name: distilhubert-finetuned-gtzan
+- name: MariaK/distilhubert-finetuned-gtzan
   results:
   - task:
       name: Audio Classification
@@ -23,18 +23,18 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.7435897435897436
+      value: 0.9
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-# distilhubert-finetuned-gtzan
+# MariaK/distilhubert-finetuned-gtzan
 
-This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
+This model is a fine-tuned version of [MariaK/distilhubert-finetuned-gtzan-v2](https://huggingface.co/MariaK/distilhubert-finetuned-gtzan-v2) on the GTZAN dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.8173
-- Accuracy: 0.7436
+- Loss: 0.3565
+- Accuracy: 0.9
 
 ## Model description
 
@@ -67,19 +67,9 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 2.1874        | 1.0   | 44   | 2.1429          | 0.3974   |
-| 1.8257        | 2.0   | 88   | 1.7390          | 0.4872   |
-| 1.4881        | 3.0   | 132  | 1.3711          | 0.6026   |
-| 1.0373        | 4.0   | 176  | 1.1632          | 0.6667   |
-| 0.7621        | 5.0   | 220  | 1.0026          | 0.7308   |
-| 0.6114        | 6.0   | 264  | 0.8857          | 0.7436   |
-| 0.5642        | 7.0   | 308  | 0.8796          | 0.7179   |
-| 0.3386        | 8.0   | 352  | 1.0714          | 0.6923   |
-| 0.3364        | 9.0   | 396  | 0.8363          | 0.7308   |
-| 0.1678        | 10.0  | 440  | 0.7834          | 0.7436   |
-| 0.1154        | 11.0  | 484  | 0.8173          | 0.7436   |
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 0.0647        | 0.9907 | 53   | 0.3565          | 0.9      |
 
 
 ### Framework versions