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: distilhubert-finetuned-gtzan
+  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
+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: 0.5833
+- Accuracy: 0.84
+
+## 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: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 5
+- total_train_batch_size: 10
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.9977        | 1.0   | 90   | 1.8501          | 0.47     |
+| 1.2442        | 2.0   | 180  | 1.2525          | 0.65     |
+| 1.1725        | 3.0   | 270  | 1.1111          | 0.68     |
+| 0.955         | 4.0   | 360  | 0.8526          | 0.74     |
+| 0.7524        | 5.0   | 450  | 0.7258          | 0.77     |
+| 0.5618        | 6.0   | 540  | 0.7356          | 0.75     |
+| 0.3265        | 7.0   | 630  | 0.6126          | 0.78     |
+| 0.3194        | 8.0   | 720  | 0.5614          | 0.84     |
+| 0.3098        | 9.0   | 810  | 0.5797          | 0.81     |
+| 0.3189        | 10.0  | 900  | 0.5833          | 0.84     |
+
+
+### Framework versions
+
+- Transformers 4.33.1
+- Pytorch 2.0.1
+- Datasets 2.4.0
+- Tokenizers 0.13.3

pytorch_model.bin

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