End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: ntu-spml/distilhubert
+tags:
+- generated_from_trainer
+datasets:
+- marsyas/gtzan
+metrics:
+- accuracy
+model-index:
+- name: distilhubert-finetuned-gtzan
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: GTZAN
+      type: marsyas/gtzan
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.82
+---
+
+<!-- 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
+
+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: 0.6341
+- Accuracy: 0.82
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.1709        | 1.0   | 57   | 2.0557          | 0.49     |
+| 1.5706        | 2.0   | 114  | 1.4771          | 0.67     |
+| 1.281         | 3.0   | 171  | 1.1843          | 0.71     |
+| 0.9681        | 4.0   | 228  | 1.0212          | 0.75     |
+| 0.8235        | 5.0   | 285  | 0.8551          | 0.8      |
+| 0.7163        | 6.0   | 342  | 0.7483          | 0.82     |
+| 0.6457        | 7.0   | 399  | 0.7269          | 0.82     |
+| 0.4788        | 8.0   | 456  | 0.6759          | 0.83     |
+| 0.4501        | 9.0   | 513  | 0.6511          | 0.82     |
+| 0.4386        | 10.0  | 570  | 0.6341          | 0.82     |
+
+
+### Framework versions
+
+- Transformers 4.46.3
+- Pytorch 2.4.1+cu121
+- Datasets 3.1.0
+- Tokenizers 0.20.3

model.safetensors

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