End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.5561797752808989
+      value: 0.42696629213483145
 ---
 
 <!-- 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: 1.3029
-- Accuracy: 0.5562
+- Loss: 1.6648
+- Accuracy: 0.4270
 
 ## Model description
 
@@ -56,8 +56,8 @@ The following hyperparameters were used during training:
 - train_batch_size: 32
 - eval_batch_size: 32
 - seed: 123
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 128
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 256
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - num_epochs: 1
@@ -66,7 +66,7 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch  | Step | Validation Loss | Accuracy |
 |:-------------:|:------:|:----:|:---------------:|:--------:|
-| No log        | 0.8696 | 5    | 1.3029          | 0.5562   |
+| No log        | 0.6957 | 2    | 1.6648          | 0.4270   |
 
 
 ### Framework versions

runs/Jul03_17-04-22_DesMar/events.out.tfevents.1720019360.DesMar.5804.1

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