End of training

README.md

@@ -5,9 +5,24 @@ tags:
 - generated_from_trainer
 datasets:
 - marsyas/gtzan
+metrics:
+- accuracy
 model-index:
 - name: distilhubert-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: 0.84
 ---
 
 <!-- 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 [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
 It achieves the following results on the evaluation set:
-- epoch: 22.12
-- eval_accuracy: 0.8
-- eval_loss: 1.0282
-- eval_runtime: 45.3044
-- eval_samples_per_second: 2.207
-- eval_steps_per_second: 0.287
-- step: 2500
+- Loss: 0.9085
+- Accuracy: 0.84
 
 ## Model description
 
@@ -42,7 +52,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 0.0005
+- learning_rate: 5e-05
 - train_batch_size: 8
 - eval_batch_size: 8
 - seed: 42
@@ -51,6 +61,39 @@ The following hyperparameters were used during training:
 - lr_scheduler_warmup_ratio: 0.1
 - training_steps: 3000
 
+### Training results
+
+| Training Loss | Epoch | Step | Accuracy | Validation Loss |
+|:-------------:|:-----:|:----:|:--------:|:---------------:|
+| 2.0825        | 0.88  | 100  | 0.47     | 1.8392          |
+| 1.4043        | 1.77  | 200  | 0.67     | 1.2675          |
+| 1.0686        | 2.65  | 300  | 0.71     | 1.0186          |
+| 0.8037        | 3.54  | 400  | 0.74     | 0.9198          |
+| 0.6215        | 4.42  | 500  | 0.78     | 0.7636          |
+| 0.5106        | 5.31  | 600  | 0.76     | 0.7937          |
+| 0.3844        | 6.19  | 700  | 0.78     | 0.6909          |
+| 0.3043        | 7.08  | 800  | 0.77     | 0.7279          |
+| 0.2453        | 7.96  | 900  | 0.82     | 0.6447          |
+| 0.211         | 8.85  | 1000 | 0.84     | 0.6404          |
+| 0.2268        | 9.73  | 1100 | 0.77     | 0.7198          |
+| 0.1565        | 10.62 | 1200 | 0.83     | 0.6704          |
+| 0.0694        | 11.5  | 1300 | 0.83     | 0.8017          |
+| 0.0568        | 12.39 | 1400 | 0.8      | 0.7841          |
+| 0.0441        | 13.27 | 1500 | 0.81     | 0.7757          |
+| 0.0302        | 14.16 | 1600 | 0.84     | 0.7819          |
+| 0.0116        | 15.04 | 1700 | 0.83     | 0.7949          |
+| 0.0289        | 15.93 | 1800 | 0.85     | 0.8057          |
+| 0.0115        | 16.81 | 1900 | 0.83     | 0.8271          |
+| 0.0081        | 17.7  | 2000 | 0.86     | 0.8005          |
+| 0.0124        | 18.58 | 2100 | 0.8      | 0.8927          |
+| 0.0219        | 19.47 | 2200 | 0.85     | 0.8126          |
+| 0.0161        | 20.35 | 2300 | 0.85     | 0.8464          |
+| 0.0157        | 21.24 | 2400 | 0.86     | 0.8459          |
+| 0.0039        | 22.12 | 2500 | 0.8      | 1.0282          |
+| 0.0145        | 23.01 | 2600 | 0.9218   | 0.84            |
+| 0.0149        | 23.89 | 2700 | 0.9085   | 0.84            |
+
+
 ### Framework versions
 
 - Transformers 4.32.0

pytorch_model.bin

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