End of training

README.md

@@ -1,4 +1,90 @@
 ---
+license: apache-2.0
+base_model: ntu-spml/distilhubert
+tags:
+- generated_from_trainer
 datasets:
 - marsyas/gtzan
----
+metrics:
+- accuracy
+model-index:
+- name: AudioCourseU4-MusicClassification
+  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: 0.86
+---
+
+<!-- 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. -->
+
+# AudioCourseU4-MusicClassification
+
+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: 1.0209
+- Accuracy: 0.86
+
+## 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: 8e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- 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
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.7993        | 1.0   | 225  | 1.5770          | 0.4      |
+| 1.0767        | 2.0   | 450  | 0.9900          | 0.7      |
+| 0.8292        | 3.0   | 675  | 0.8554          | 0.73     |
+| 0.5892        | 4.0   | 900  | 0.8991          | 0.74     |
+| 0.1584        | 5.0   | 1125 | 0.8473          | 0.78     |
+| 0.0082        | 6.0   | 1350 | 0.9282          | 0.8      |
+| 0.0094        | 7.0   | 1575 | 1.0036          | 0.82     |
+| 0.0581        | 8.0   | 1800 | 1.2186          | 0.82     |
+| 0.0021        | 9.0   | 2025 | 1.0192          | 0.83     |
+| 0.0011        | 10.0  | 2250 | 0.8804          | 0.88     |
+| 0.002         | 11.0  | 2475 | 1.1519          | 0.83     |
+| 0.0009        | 12.0  | 2700 | 0.9439          | 0.87     |
+| 0.0006        | 13.0  | 2925 | 1.1227          | 0.84     |
+| 0.0008        | 14.0  | 3150 | 1.0344          | 0.86     |
+| 0.0006        | 15.0  | 3375 | 1.0209          | 0.86     |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.4
+- Tokenizers 0.13.3

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