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: 0.92
+---
+
+<!-- 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: 0.2954
+- Accuracy: 0.92
+
+## 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: 20
+- eval_batch_size: 20
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 80
+- 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 |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 1.9615        | 0.9778 | 11   | 0.8039          | 0.81     |
+| 0.6265        | 1.9556 | 22   | 0.5248          | 0.84     |
+| 0.3419        | 2.9333 | 33   | 0.5014          | 0.81     |
+| 0.172         | 4.0    | 45   | 0.3780          | 0.91     |
+| 0.0895        | 4.9778 | 56   | 0.4103          | 0.85     |
+| 0.033         | 5.9556 | 67   | 0.3093          | 0.9      |
+| 0.0173        | 6.9333 | 78   | 0.2954          | 0.92     |
+| 0.0083        | 8.0    | 90   | 0.3354          | 0.88     |
+| 0.0042        | 8.9778 | 101  | 0.2688          | 0.92     |
+| 0.001         | 9.7778 | 110  | 0.2712          | 0.92     |
+
+
+### Framework versions
+
+- Transformers 4.44.0
+- Pytorch 2.4.0
+- Datasets 2.21.0
+- Tokenizers 0.19.1

model.safetensors

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