End of training

README.md

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+---
+license: bsd-3-clause
+base_model: MIT/ast-finetuned-audioset-10-10-0.4593
+tags:
+- generated_from_trainer
+datasets:
+- marsyas/gtzan
+metrics:
+- accuracy
+model-index:
+- name: ast-finetuned-audioset-10-10-0.4593-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: 0.87
+---
+
+<!-- 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. -->
+
+# ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan
+
+This model is a fine-tuned version of [MIT/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593) on the GTZAN dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8005
+- Accuracy: 0.87
+
+## 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
+- 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
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.1235        | 1.0   | 450  | 0.7646          | 0.78     |
+| 0.8603        | 2.0   | 900  | 0.8960          | 0.79     |
+| 0.0102        | 3.0   | 1350 | 1.0994          | 0.75     |
+| 0.9165        | 4.0   | 1800 | 0.7021          | 0.86     |
+| 0.0004        | 5.0   | 2250 | 0.7447          | 0.86     |
+| 0.0           | 6.0   | 2700 | 0.6903          | 0.87     |
+| 1.1203        | 7.0   | 3150 | 0.8936          | 0.86     |
+| 0.0           | 8.0   | 3600 | 0.8538          | 0.87     |
+| 0.0           | 9.0   | 4050 | 0.8081          | 0.87     |
+| 0.0           | 10.0  | 4500 | 0.8005          | 0.87     |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0

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