End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.20833333333333334
+      value: 0.2708333333333333
 ---
 
 <!-- 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 audiofolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.9825
-- Accuracy: 0.2083
+- Loss: 1.9466
+- Accuracy: 0.2708
 
 ## Model description
 
@@ -58,29 +58,26 @@ The following hyperparameters were used during training:
 - 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
+- lr_scheduler_warmup_ratio: 0.8
+- num_epochs: 12
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 2.4542        | 1.0   | 48   | 2.4501          | 0.1354   |
-| 2.499         | 2.0   | 96   | 2.4186          | 0.1042   |
-| 2.4441        | 3.0   | 144  | 2.3464          | 0.1875   |
-| 2.1364        | 4.0   | 192  | 2.2214          | 0.2083   |
-| 1.9561        | 5.0   | 240  | 2.1193          | 0.1771   |
-| 2.05          | 6.0   | 288  | 2.0221          | 0.1875   |
-| 1.7704        | 7.0   | 336  | 2.0434          | 0.1771   |
-| 1.8652        | 8.0   | 384  | 1.9728          | 0.1875   |
-| 1.77          | 9.0   | 432  | 1.9415          | 0.2292   |
-| 1.6381        | 10.0  | 480  | 2.0323          | 0.1562   |
-| 1.6316        | 11.0  | 528  | 1.9657          | 0.2292   |
-| 1.504         | 12.0  | 576  | 1.9644          | 0.1875   |
-| 1.3872        | 13.0  | 624  | 1.9719          | 0.2292   |
-| 1.3829        | 14.0  | 672  | 1.9794          | 0.1979   |
-| 1.3251        | 15.0  | 720  | 1.9825          | 0.2083   |
+| 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   |
 
 
 ### Framework versions