End of training

README.md

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+---
+license: apache-2.0
+base_model: ntu-spml/distilhubert
+tags:
+- generated_from_trainer
+datasets:
+- marsyas/gtzan
+metrics:
+- accuracy
+model-index:
+- name: 25-distilhubert-finetuned-gtzan
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: GTZAN
+      type: marsyas/gtzan
+      config: default
+      split: train[:25%]
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.96
+---
+
+<!-- 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. -->
+
+# 25-distilhubert-finetuned-gtzan
+
+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: 0.1955
+- Accuracy: 0.96
+
+## 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: 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: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.3123        | 1.0   | 57   | 1.3463          | 0.56     |
+| 0.6113        | 2.0   | 114  | 0.5379          | 0.96     |
+| 0.1295        | 3.0   | 171  | 0.2719          | 0.96     |
+| 0.2878        | 4.0   | 228  | 0.0979          | 0.96     |
+| 0.0168        | 5.0   | 285  | 0.1527          | 0.96     |
+| 0.0104        | 6.0   | 342  | 0.2320          | 0.96     |
+| 0.0067        | 7.0   | 399  | 0.1798          | 0.96     |
+| 0.0051        | 8.0   | 456  | 0.1827          | 0.96     |
+| 0.0041        | 9.0   | 513  | 0.1918          | 0.96     |
+| 0.0055        | 10.0  | 570  | 0.1955          | 0.96     |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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