End of training

README.md

@@ -5,9 +5,24 @@ tags:
 - generated_from_trainer
 datasets:
 - audiofolder
+metrics:
+- accuracy
 model-index:
 - name: distilhubert-finetuned-cry-detector
-  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: 0.7191011235955056
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,6 +31,9 @@ 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: 1.1308
+- Accuracy: 0.7191
 
 ## Model description
 
@@ -42,13 +60,15 @@ 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: 1
+- num_epochs: 3
 
 ### Training results
 
 | Training Loss | Epoch  | Step | Validation Loss | Accuracy |
 |:-------------:|:------:|:----:|:---------------:|:--------:|
-| No log        | 0.9888 | 11   | 1.6532          | 0.5506   |
+| No log        | 0.9888 | 11   | 1.4269          | 0.5674   |
+| No log        | 1.9775 | 22   | 1.1754          | 0.7022   |
+| No log        | 2.9663 | 33   | 1.1308          | 0.7191   |
 
 
 ### Framework versions

model.safetensors

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 size 94770700

runs/Aug07_17-19-41_DesMar/events.out.tfevents.1723043982.DesMar.8692.0

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training_args.bin

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