update model card README.md

README.md

@@ -1,6 +1,6 @@
 ---
 license: apache-2.0
-base_model: ntu-spml/distilhubert
+base_model: Sandiago21/distilhubert-finetuned-gtzan
 tags:
 - generated_from_trainer
 datasets:
@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.83
+      value: 0.85
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -30,10 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # distilhubert-finetuned-gtzan
 
-This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
+This model is a fine-tuned version of [Sandiago21/distilhubert-finetuned-gtzan](https://huggingface.co/Sandiago21/distilhubert-finetuned-gtzan) on the GTZAN dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.8934
-- Accuracy: 0.83
+- Loss: 0.9021
+- Accuracy: 0.85
 
 ## Model description
 
@@ -53,38 +53,33 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 0.0001
-- train_batch_size: 8
-- eval_batch_size: 8
+- train_batch_size: 16
+- eval_batch_size: 16
 - 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: 15
+- num_epochs: 10
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.9361        | 1.0   | 113  | 1.7009          | 0.47     |
-| 1.2014        | 2.0   | 226  | 1.0356          | 0.68     |
-| 0.943         | 3.0   | 339  | 0.8529          | 0.76     |
-| 0.6362        | 4.0   | 452  | 0.9040          | 0.72     |
-| 0.4754        | 5.0   | 565  | 0.7102          | 0.79     |
-| 0.4526        | 6.0   | 678  | 0.6811          | 0.8      |
-| 0.2139        | 7.0   | 791  | 0.7872          | 0.83     |
-| 0.0133        | 8.0   | 904  | 0.8736          | 0.83     |
-| 0.0089        | 9.0   | 1017 | 0.8696          | 0.82     |
-| 0.0639        | 10.0  | 1130 | 0.9064          | 0.85     |
-| 0.0026        | 11.0  | 1243 | 0.9165          | 0.82     |
-| 0.1601        | 12.0  | 1356 | 0.8257          | 0.86     |
-| 0.0017        | 13.0  | 1469 | 0.8388          | 0.85     |
-| 0.0018        | 14.0  | 1582 | 0.8639          | 0.84     |
-| 0.0017        | 15.0  | 1695 | 0.8934          | 0.83     |
+| 0.2617        | 1.0   | 57   | 0.8101          | 0.76     |
+| 0.3005        | 2.0   | 114  | 0.8589          | 0.82     |
+| 0.0123        | 3.0   | 171  | 1.0596          | 0.8      |
+| 0.0141        | 4.0   | 228  | 1.0238          | 0.81     |
+| 0.0047        | 5.0   | 285  | 0.8953          | 0.83     |
+| 0.0889        | 6.0   | 342  | 0.8765          | 0.86     |
+| 0.0482        | 7.0   | 399  | 1.1115          | 0.83     |
+| 0.0013        | 8.0   | 456  | 1.0884          | 0.84     |
+| 0.0009        | 9.0   | 513  | 1.0055          | 0.85     |
+| 0.0008        | 10.0  | 570  | 0.9021          | 0.85     |
 
 
 ### Framework versions
 
-- Transformers 4.32.0.dev0
+- Transformers 4.31.0
 - Pytorch 2.0.1+cu118
 - Datasets 2.14.3
 - Tokenizers 0.13.3