End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.6853932584269663
+      value: 0.6966292134831461
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 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: 0.9077
-- Accuracy: 0.6854
+- Loss: 0.9121
+- Accuracy: 0.6966
 
 ## Model description
 
@@ -53,10 +53,10 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 0.001
-- train_batch_size: 16
-- eval_batch_size: 16
+- train_batch_size: 8
+- eval_batch_size: 8
 - seed: 123
-- gradient_accumulation_steps: 4
+- 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
@@ -66,7 +66,7 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch  | Step | Validation Loss | Accuracy |
 |:-------------:|:------:|:----:|:---------------:|:--------:|
-| No log        | 0.9778 | 11   | 0.9077          | 0.6854   |
+| No log        | 0.9888 | 11   | 0.9121          | 0.6966   |
 
 
 ### Framework versions

runs/Jul03_17-22-51_DesMar/events.out.tfevents.1720020173.DesMar.5308.0

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-size 6072
+oid sha256:9934c9ee9cf3c2dff4a48deed842332739a5ad5163383565dcd8364fa95d2241
+size 6737

runs/Jul03_17-22-51_DesMar/events.out.tfevents.1720020273.DesMar.5308.1

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