End of training

README.md

@@ -6,36 +6,9 @@ tags:
 - generated_from_trainer
 datasets:
 - audiofolder
-metrics:
-- accuracy
-- f1
-- precision
-- recall
 model-index:
 - name: distilhubert-finetuned-cry-detector
-  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: 0.9852941176470589
-    - name: F1
-      type: f1
-      value: 0.9853150765112866
-    - name: Precision
-      type: precision
-      value: 0.9853868369053048
-    - name: Recall
-      type: recall
-      value: 0.9852941176470589
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -44,12 +17,6 @@ should probably proofread and complete it, then remove this comment. -->
 # distilhubert-finetuned-cry-detector
 
 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: 0.0332
-- Accuracy: 0.9853
-- F1: 0.9853
-- Precision: 0.9854
-- Recall: 0.9853
 
 ## Model description
 
@@ -77,22 +44,13 @@ 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: 10
+- num_epochs: 1
 
 ### Training results
 
 | Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
 |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
-| No log        | 0.9412 | 12   | 0.1931          | 0.9363   | 0.9365 | 0.9372    | 0.9363 |
-| No log        | 1.9608 | 25   | 0.0950          | 0.9706   | 0.9704 | 0.9710    | 0.9706 |
-| No log        | 2.9804 | 38   | 0.0611          | 0.9804   | 0.9804 | 0.9804    | 0.9804 |
-| No log        | 4.0    | 51   | 0.0492          | 0.9853   | 0.9853 | 0.9853    | 0.9853 |
-| No log        | 4.9412 | 63   | 0.0588          | 0.9804   | 0.9805 | 0.9814    | 0.9804 |
-| No log        | 5.9608 | 76   | 0.0368          | 0.9853   | 0.9853 | 0.9854    | 0.9853 |
-| No log        | 6.9804 | 89   | 0.0382          | 0.9902   | 0.9902 | 0.9903    | 0.9902 |
-| No log        | 8.0    | 102  | 0.0318          | 0.9951   | 0.9951 | 0.9951    | 0.9951 |
-| No log        | 8.9412 | 114  | 0.0331          | 0.9853   | 0.9853 | 0.9854    | 0.9853 |
-| No log        | 9.4118 | 120  | 0.0332          | 0.9853   | 0.9853 | 0.9854    | 0.9853 |
+| No log        | 0.9956 | 85   | 0.1014          | 0.9641   | 0.9642 | 0.9643    | 0.9641 |
 
 
 ### Framework versions

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