Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: ntu-spml/distilhubert
+tags:
+- generated_from_trainer
+datasets:
+- gtzan
+metrics:
+- accuracy
+model-index:
+- name: distilhubert-finetuned_gtzan
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: gtzan
+      type: gtzan
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.75
+---
+
+<!-- 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: 0.8025
+- Accuracy: 0.75
+
+## 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: 8
+- eval_batch_size: 8
+- 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: 7
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.7782        | 1.0   | 113  | 1.7870          | 0.49     |
+| 1.2942        | 2.0   | 226  | 1.3317          | 0.62     |
+| 1.0869        | 3.0   | 339  | 1.0283          | 0.73     |
+| 0.5358        | 4.0   | 452  | 0.9647          | 0.72     |
+| 0.6048        | 5.0   | 565  | 0.7985          | 0.76     |
+| 0.4135        | 6.0   | 678  | 0.8013          | 0.75     |
+| 0.3721        | 7.0   | 791  | 0.8025          | 0.75     |
+
+
+### Framework versions
+
+- Transformers 4.47.0
+- Pytorch 2.5.1
+- Datasets 2.19.1
+- Tokenizers 0.21.0

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