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: 0.9691629955947136
-    - name: F1
-      type: f1
-      value: 0.9692159230090303
-    - name: Precision
-      type: precision
-      value: 0.969310997758714
-    - name: Recall
-      type: recall
-      value: 0.9691629955947136
+  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: 0.0854
-- Accuracy: 0.9692
-- F1: 0.9692
-- Precision: 0.9693
-- Recall: 0.9692
 
 ## Model description
 
@@ -76,17 +43,14 @@ The following hyperparameters were used during training:
 - total_train_batch_size: 64
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: cosine
-- num_epochs: 5
+- lr_scheduler_warmup_ratio: 0.001
+- num_epochs: 1
 
 ### Training results
 
 | Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
 |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
-| No log        | 0.9825 | 14   | 0.1771          | 0.9339   | 0.9348 | 0.9388    | 0.9339 |
-| No log        | 1.9649 | 28   | 0.1569          | 0.9427   | 0.9434 | 0.9459    | 0.9427 |
-| No log        | 2.9474 | 42   | 0.1216          | 0.9559   | 0.9556 | 0.9560    | 0.9559 |
-| No log        | 4.0    | 57   | 0.0876          | 0.9692   | 0.9692 | 0.9693    | 0.9692 |
-| No log        | 4.9123 | 70   | 0.0854          | 0.9692   | 0.9692 | 0.9693    | 0.9692 |
+| No log        | 0.9825 | 14   | 0.3061          | 0.9515   | 0.9513 | 0.9514    | 0.9515 |
 
 
 ### Framework versions

model.safetensors

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