update model card README.md

README.md

@@ -5,9 +5,24 @@ tags:
 - generated_from_trainer
 datasets:
 - marsyas/gtzan
+metrics:
+- accuracy
 model-index:
 - name: distil-ast-audioset-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: 0.85
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -17,13 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [bookbot/distil-ast-audioset](https://huggingface.co/bookbot/distil-ast-audioset) on the GTZAN dataset.
 It achieves the following results on the evaluation set:
-- eval_loss: 2.0566
-- eval_accuracy: 0.55
-- eval_runtime: 10.1124
-- eval_samples_per_second: 9.889
-- eval_steps_per_second: 1.286
-- epoch: 19.0
-- step: 2147
+- Loss: 0.6033
+- Accuracy: 0.85
 
 ## Model description
 
@@ -49,7 +59,23 @@ 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: 20
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.2238        | 1.0   | 113  | 0.8023          | 0.75     |
+| 0.6623        | 2.0   | 226  | 0.6611          | 0.79     |
+| 0.9376        | 3.0   | 339  | 0.6243          | 0.81     |
+| 0.3924        | 4.0   | 452  | 0.6123          | 0.85     |
+| 0.2442        | 5.0   | 565  | 0.5983          | 0.83     |
+| 0.1408        | 6.0   | 678  | 0.6270          | 0.84     |
+| 0.2874        | 7.0   | 791  | 0.7019          | 0.78     |
+| 0.0177        | 8.0   | 904  | 0.6482          | 0.83     |
+| 0.036         | 9.0   | 1017 | 0.5012          | 0.88     |
+| 0.0013        | 10.0  | 1130 | 0.6033          | 0.85     |
+
 
 ### Framework versions