update model card README.md

README.md

@@ -0,0 +1,95 @@
+---
+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-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: 0.89
+---
+
+<!-- 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-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: 0.6261
+- Accuracy: 0.89
+
+## 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: 4
+- eval_batch_size: 4
+- 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: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.03          | 1.0   | 225  | 0.7218          | 0.81     |
+| 0.3004        | 2.0   | 450  | 1.1639          | 0.8      |
+| 0.5633        | 3.0   | 675  | 0.8839          | 0.83     |
+| 0.0354        | 4.0   | 900  | 0.8839          | 0.8      |
+| 0.5666        | 5.0   | 1125 | 1.1155          | 0.82     |
+| 0.0001        | 6.0   | 1350 | 0.6813          | 0.9      |
+| 0.2482        | 7.0   | 1575 | 0.6845          | 0.9      |
+| 0.0001        | 8.0   | 1800 | 1.4196          | 0.8      |
+| 0.0           | 9.0   | 2025 | 0.9603          | 0.84     |
+| 0.0           | 10.0  | 2250 | 0.7030          | 0.88     |
+| 0.0           | 11.0  | 2475 | 0.6363          | 0.89     |
+| 0.0           | 12.0  | 2700 | 0.6589          | 0.89     |
+| 0.0           | 13.0  | 2925 | 0.6845          | 0.87     |
+| 0.0           | 14.0  | 3150 | 0.6061          | 0.9      |
+| 0.0           | 15.0  | 3375 | 0.6210          | 0.89     |
+| 0.0           | 16.0  | 3600 | 0.6136          | 0.89     |
+| 0.0           | 17.0  | 3825 | 0.6104          | 0.89     |
+| 0.0           | 18.0  | 4050 | 0.6147          | 0.89     |
+| 0.0           | 19.0  | 4275 | 0.6259          | 0.89     |
+| 0.0           | 20.0  | 4500 | 0.6261          | 0.89     |
+
+
+### Framework versions
+
+- Transformers 4.32.0.dev0
+- Pytorch 2.0.1+cu118
+- Datasets 2.13.1
+- Tokenizers 0.13.3