update model card README.md

README.md

@@ -4,9 +4,24 @@ tags:
 - generated_from_trainer
 datasets:
 - marsyas/gtzan
+metrics:
+- accuracy
 model-index:
 - name: distilhubert-finetuned-gtzan
-  results: []
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: GTZAN
+      type: marsyas/gtzan
+      config: all
+      split: train
+      args: all
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8823529411764706
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,13 +31,8 @@ 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:
-- eval_loss: 0.5092
-- eval_accuracy: 0.8824
-- eval_runtime: 17.8602
-- eval_samples_per_second: 1.904
-- eval_steps_per_second: 0.504
-- epoch: 2.0
-- step: 150
+- Loss: 0.8092
+- Accuracy: 0.8824
 
 ## Model description
 
@@ -42,13 +52,22 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-05
-- train_batch_size: 4
-- eval_batch_size: 4
+- train_batch_size: 8
+- eval_batch_size: 8
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 13
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.5308        | 1.0   | 38   | 1.4348          | 0.6471   |
+| 1.0143        | 2.0   | 76   | 0.9504          | 0.8824   |
+| 0.8684        | 3.0   | 114  | 0.8092          | 0.8824   |
+
 
 ### Framework versions