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-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: 0.7317073170731707
-    - name: F1
-      type: f1
-      value: 0.6183442116111302
-    - name: Precision
-      type: precision
-      value: 0.5353955978584176
-    - name: Recall
-      type: recall
-      value: 0.7317073170731707
+  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-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: 0.9804
-- Accuracy: 0.7317
-- F1: 0.6183
-- Precision: 0.5354
-- Recall: 0.7317
 
 ## Model description
 
@@ -77,14 +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: 2
+- num_epochs: 1
 
 ### Training results
 
 | Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
 |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
-| No log        | 0.9032 | 7    | 1.0560          | 0.7154   | 0.6354 | 0.5727    | 0.7154 |
-| No log        | 1.8065 | 14   | 0.9804          | 0.7317   | 0.6183 | 0.5354    | 0.7317 |
+| No log        | 0.9032 | 7    | 1.0438          | 0.7317   | 0.6183 | 0.5354    | 0.7317 |
 
 
 ### Framework versions

model.safetensors

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