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: 0.88
+---
+
+<!-- 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: 0.6087
+- Accuracy: 0.88
+
+## 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: 4
+- total_train_batch_size: 8
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 20
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.9526        | 1.0   | 112  | 1.8797          | 0.74     |
+| 0.9704        | 2.0   | 225  | 1.0561          | 0.7      |
+| 0.7957        | 3.0   | 337  | 0.7362          | 0.77     |
+| 0.4428        | 4.0   | 450  | 0.7820          | 0.8      |
+| 0.1422        | 5.0   | 562  | 0.6142          | 0.84     |
+| 0.3502        | 6.0   | 675  | 0.9189          | 0.82     |
+| 0.01          | 7.0   | 787  | 0.7735          | 0.83     |
+| 0.0068        | 8.0   | 900  | 1.0699          | 0.81     |
+| 0.1751        | 9.0   | 1012 | 0.5360          | 0.88     |
+| 0.0045        | 10.0  | 1125 | 0.5377          | 0.89     |
+| 0.154         | 11.0  | 1237 | 0.6542          | 0.86     |
+| 0.0025        | 12.0  | 1350 | 0.6206          | 0.89     |
+| 0.0022        | 13.0  | 1462 | 0.6118          | 0.88     |
+| 0.0021        | 14.0  | 1575 | 0.5961          | 0.89     |
+| 0.0018        | 15.0  | 1687 | 0.5958          | 0.88     |
+| 0.0017        | 16.0  | 1800 | 0.6062          | 0.88     |
+| 0.0017        | 17.0  | 1912 | 0.6005          | 0.88     |
+| 0.0015        | 18.0  | 2025 | 0.6052          | 0.88     |
+| 0.0014        | 19.0  | 2137 | 0.6114          | 0.88     |
+| 0.0015        | 19.91 | 2240 | 0.6087          | 0.88     |
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- Pytorch 2.1.2+cu118
+- Datasets 2.16.1
+- Tokenizers 0.15.0

model.safetensors

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