End of training

README.md

@@ -0,0 +1,86 @@
+---
+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: 0.9
+---
+
+<!-- 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: 0.7292
+- Accuracy: 0.9
+
+## 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: 8
+- eval_batch_size: 8
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.0564        | 1.0   | 113  | 0.6135          | 0.83     |
+| 0.3513        | 2.0   | 226  | 0.5031          | 0.87     |
+| 0.3781        | 3.0   | 339  | 0.4387          | 0.89     |
+| 0.0142        | 4.0   | 452  | 0.6148          | 0.89     |
+| 0.188         | 5.0   | 565  | 0.8578          | 0.88     |
+| 0.0           | 6.0   | 678  | 1.0513          | 0.89     |
+| 0.4527        | 7.0   | 791  | 0.9157          | 0.88     |
+| 0.0           | 8.0   | 904  | 1.0898          | 0.85     |
+| 0.0           | 9.0   | 1017 | 0.7875          | 0.89     |
+| 0.0           | 10.0  | 1130 | 0.7292          | 0.9      |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.2
+- Datasets 2.17.0
+- Tokenizers 0.15.1