End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.85
+      value: 0.86
 ---
 
 <!-- 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 GTZAN dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.5773
-- Accuracy: 0.85
+- Loss: 0.5698
+- Accuracy: 0.86
 
 ## Model description
 
@@ -52,7 +52,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 3e-05
+- learning_rate: 5e-05
 - train_batch_size: 4
 - eval_batch_size: 4
 - seed: 42
@@ -61,15 +61,16 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 3
+- num_epochs: 4
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.0808        | 1.0   | 75   | 0.5747          | 0.84     |
-| 0.0497        | 2.0   | 150  | 0.7134          | 0.81     |
-| 0.0733        | 3.0   | 225  | 0.5773          | 0.85     |
+| 0.5773        | 1.0   | 75   | 0.7146          | 0.84     |
+| 0.4322        | 2.0   | 150  | 0.6362          | 0.82     |
+| 0.445         | 3.0   | 225  | 0.5768          | 0.88     |
+| 0.2764        | 4.0   | 300  | 0.5698          | 0.86     |
 
 
 ### Framework versions

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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+oid sha256:9b7643580decf6d9264f48e1cd90e6e215d7c1199d2ad2ca0f6a1d3deb48844a
 size 94783376