End of training

README.md

@@ -8,7 +8,7 @@ datasets:
 metrics:
 - accuracy
 model-index:
-- name: distilhubert-finetuned-gtzan
+- name: distilhubert-finetuned-gtzan-30-epochs
   results:
   - task:
       name: Audio Classification
@@ -22,18 +22,18 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.11
+      value: 0.81
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-# distilhubert-finetuned-gtzan
+# distilhubert-finetuned-gtzan-30-epochs
 
 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:
-- Loss: 2.3061
-- Accuracy: 0.11
+- Loss: 1.1939
+- Accuracy: 0.81
 
 ## Model description
 
@@ -53,24 +53,53 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-05
-- train_batch_size: 1
-- eval_batch_size: 1
+- 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: 1
+- num_epochs: 30
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 2.3978        | 1.0   | 899  | 2.3061          | 0.11     |
+| 2.1804        | 1.0   | 113  | 2.1756          | 0.46     |
+| 1.7271        | 2.0   | 226  | 1.6973          | 0.53     |
+| 1.2703        | 3.0   | 339  | 1.2950          | 0.51     |
+| 0.9446        | 4.0   | 452  | 0.9433          | 0.68     |
+| 0.6192        | 5.0   | 565  | 0.7885          | 0.73     |
+| 0.3628        | 6.0   | 678  | 0.8338          | 0.76     |
+| 0.2871        | 7.0   | 791  | 0.8125          | 0.74     |
+| 0.0587        | 8.0   | 904  | 0.7500          | 0.8      |
+| 0.1316        | 9.0   | 1017 | 0.8711          | 0.79     |
+| 0.0175        | 10.0  | 1130 | 0.7429          | 0.82     |
+| 0.0818        | 11.0  | 1243 | 0.9848          | 0.81     |
+| 0.0049        | 12.0  | 1356 | 1.0498          | 0.76     |
+| 0.0034        | 13.0  | 1469 | 1.0422          | 0.84     |
+| 0.0028        | 14.0  | 1582 | 1.0919          | 0.83     |
+| 0.0023        | 15.0  | 1695 | 1.0565          | 0.82     |
+| 0.0019        | 16.0  | 1808 | 1.0797          | 0.84     |
+| 0.0769        | 17.0  | 1921 | 1.1430          | 0.82     |
+| 0.104         | 18.0  | 2034 | 1.1482          | 0.8      |
+| 0.0014        | 19.0  | 2147 | 1.0972          | 0.83     |
+| 0.0012        | 20.0  | 2260 | 1.1867          | 0.82     |
+| 0.0012        | 21.0  | 2373 | 1.1914          | 0.82     |
+| 0.0012        | 22.0  | 2486 | 1.1461          | 0.84     |
+| 0.0009        | 23.0  | 2599 | 1.1401          | 0.82     |
+| 0.0009        | 24.0  | 2712 | 1.1686          | 0.84     |
+| 0.0009        | 25.0  | 2825 | 1.1824          | 0.85     |
+| 0.0009        | 26.0  | 2938 | 1.1815          | 0.81     |
+| 0.0008        | 27.0  | 3051 | 1.1808          | 0.82     |
+| 0.0008        | 28.0  | 3164 | 1.1904          | 0.81     |
+| 0.0008        | 29.0  | 3277 | 1.1990          | 0.82     |
+| 0.0008        | 30.0  | 3390 | 1.1939          | 0.81     |
 
 
 ### Framework versions
 
 - Transformers 4.33.0.dev0
-- Pytorch 2.0.1
-- Datasets 2.12.0
-- Tokenizers 0.13.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.4
+- Tokenizers 0.13.3

pytorch_model.bin

@@ -1,3 +1,3 @@
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+oid sha256:98ef95f2eeee30150ffe68fdbbf4bdca389410211416308ace36a75b4977070d
 size 94783376