End of training

README.md

@@ -6,9 +6,36 @@ tags:
 - generated_from_trainer
 datasets:
 - audiofolder
+metrics:
+- accuracy
+- f1
+- precision
+- recall
 model-index:
 - name: distilhubert-finetuned-mixed-data
-  results: []
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: audiofolder
+      type: audiofolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.889261744966443
+    - name: F1
+      type: f1
+      value: 0.8883742273982193
+    - name: Precision
+      type: precision
+      value: 0.8879660679296787
+    - name: Recall
+      type: recall
+      value: 0.889261744966443
 ---
 
 <!-- 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. -->
 # distilhubert-finetuned-mixed-data
 
 This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the audiofolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2853
+- Accuracy: 0.8893
+- F1: 0.8884
+- Precision: 0.8880
+- Recall: 0.8893
 
 ## Model description
 
@@ -44,13 +77,22 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: cosine
 - lr_scheduler_warmup_ratio: 0.001
-- num_epochs: 1
+- num_epochs: 10
 
 ### Training results
 
 | Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
 |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
-| No log        | 0.9664 | 18   | 0.9849          | 0.6879   | 0.6341 | 0.5921    | 0.6879 |
+| No log        | 0.9664 | 18   | 0.6892          | 0.7617   | 0.7077 | 0.6737    | 0.7617 |
+| No log        | 1.9866 | 37   | 0.5095          | 0.8087   | 0.7505 | 0.7108    | 0.8087 |
+| No log        | 2.9530 | 55   | 0.4728          | 0.7819   | 0.7226 | 0.6874    | 0.7819 |
+| No log        | 3.9732 | 74   | 0.3589          | 0.8658   | 0.8559 | 0.8575    | 0.8658 |
+| No log        | 4.9933 | 93   | 0.3575          | 0.8456   | 0.8440 | 0.8494    | 0.8456 |
+| No log        | 5.9597 | 111  | 0.3389          | 0.8557   | 0.8550 | 0.8720    | 0.8557 |
+| No log        | 6.9799 | 130  | 0.3046          | 0.8725   | 0.8723 | 0.8766    | 0.8725 |
+| No log        | 8.0    | 149  | 0.2980          | 0.8826   | 0.8814 | 0.8820    | 0.8826 |
+| No log        | 8.9664 | 167  | 0.2848          | 0.8859   | 0.8848 | 0.8840    | 0.8859 |
+| No log        | 9.6644 | 180  | 0.2853          | 0.8893   | 0.8884 | 0.8880    | 0.8893 |
 
 
 ### Framework versions

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