End of training

README.md

@@ -5,24 +5,9 @@ tags:
 - generated_from_trainer
 datasets:
 - audiofolder
-metrics:
-- accuracy
 model-index:
 - name: distilhubert-finetuned-donateacry
-  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: 0.5617977528089888
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,9 +16,6 @@ should probably proofread and complete it, then remove this comment. -->
 # distilhubert-finetuned-donateacry
 
 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: 1.6585
-- Accuracy: 0.5618
 
 ## Model description
 
@@ -59,14 +41,14 @@ The following hyperparameters were used during training:
 - gradient_accumulation_steps: 8
 - total_train_batch_size: 64
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
+- lr_scheduler_type: cosine
 - num_epochs: 1
 
 ### Training results
 
 | Training Loss | Epoch  | Step | Validation Loss | Accuracy |
 |:-------------:|:------:|:----:|:---------------:|:--------:|
-| No log        | 0.9888 | 11   | 1.6585          | 0.5618   |
+| No log        | 0.9888 | 11   | 1.6532          | 0.5506   |
 
 
 ### Framework versions

label_mappings.json

@@ -0,0 +1 @@
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training_args.bin

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