Training in progress, epoch 1

.ipynb_checkpoints/README-checkpoint.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: 0.86
+---
+
+<!-- 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. -->
+
+# 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: 0.5269
+- 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: 0.0001
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.9286        | 0.99  | 56   | 1.7845          | 0.56     |
+| 1.2162        | 2.0   | 113  | 1.1310          | 0.74     |
+| 0.8715        | 2.99  | 169  | 0.8334          | 0.75     |
+| 0.6735        | 4.0   | 226  | 0.7352          | 0.79     |
+| 0.4007        | 4.99  | 282  | 0.5135          | 0.87     |
+| 0.241         | 6.0   | 339  | 0.7801          | 0.76     |
+| 0.181         | 6.99  | 395  | 0.5440          | 0.81     |
+| 0.1336        | 8.0   | 452  | 0.5280          | 0.85     |
+| 0.0526        | 8.99  | 508  | 0.4992          | 0.87     |
+| 0.0315        | 9.91  | 560  | 0.5269          | 0.86     |
+
+
+### Framework versions
+
+- Transformers 4.32.0.dev0
+- Pytorch 2.0.1
+- Datasets 2.13.1
+- Tokenizers 0.13.3

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