Restore new model card

README.md

@@ -32,52 +32,35 @@ 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: 1.9466
+- Loss: 2.0748
 - Accuracy: 0.2708
 
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 5e-05
-- train_batch_size: 8
-- eval_batch_size: 8
-- seed: 42
+ ## Model description
+ - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- lr_scheduler_warmup_ratio: 0.8
-- num_epochs: 12
+- lr_scheduler_warmup_ratio: 0.7
+- num_epochs: 14
 - mixed_precision_training: Native AMP
 
-### Training results
+ ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 2.48          | 1.0   | 48   | 2.4777          | 0.1042   |
-| 2.473         | 2.0   | 96   | 2.4604          | 0.1562   |
-| 2.4772        | 3.0   | 144  | 2.4282          | 0.1042   |
-| 2.3678        | 4.0   | 192  | 2.4007          | 0.1042   |
-| 2.324         | 5.0   | 240  | 2.3261          | 0.2083   |
-| 2.2489        | 6.0   | 288  | 2.2360          | 0.1771   |
-| 1.9909        | 7.0   | 336  | 2.1544          | 0.1875   |
-| 1.9903        | 8.0   | 384  | 2.0937          | 0.1875   |
-| 2.0668        | 9.0   | 432  | 2.0222          | 0.2083   |
-| 1.8473        | 10.0  | 480  | 2.0298          | 0.1875   |
-| 1.8068        | 11.0  | 528  | 1.9965          | 0.25     |
-| 1.699         | 12.0  | 576  | 1.9466          | 0.2708   |
+| 2.4778        | 1.0   | 48   | 2.4807          | 0.0938   |
+| 2.4779        | 2.0   | 96   | 2.4651          | 0.1042   |
+| 2.4751        | 3.0   | 144  | 2.4365          | 0.1042   |
+| 2.3777        | 4.0   | 192  | 2.4187          | 0.1042   |
+| 2.3786        | 5.0   | 240  | 2.4050          | 0.1458   |
+| 2.3754        | 6.0   | 288  | 2.3446          | 0.1458   |
+| 2.1556        | 7.0   | 336  | 2.2284          | 0.2083   |
+| 2.1062        | 8.0   | 384  | 2.1533          | 0.2188   |
+| 2.0081        | 9.0   | 432  | 2.0765          | 0.2292   |
+| 1.813         | 10.0  | 480  | 2.0671          | 0.2083   |
+| 1.74          | 11.0  | 528  | 1.9977          | 0.3021   |
+| 1.4795        | 12.0  | 576  | 2.0588          | 0.2396   |
+| 1.298         | 13.0  | 624  | 2.0652          | 0.3021   |
+| 1.2578        | 14.0  | 672  | 2.0748          | 0.2708   |
 
 
 ### Framework versions