End of training

README.md

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+---
+base_model: yus988/pingpong-music_genres_classification-finetuned
+tags:
+- generated_from_trainer
+datasets:
+- marsyas/gtzan
+metrics:
+- accuracy
+model-index:
+- name: pingpong-music_genres_classification-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: 0.94
+---
+
+<!-- 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. -->
+
+# pingpong-music_genres_classification-finetuned-gtzan
+
+This model is a fine-tuned version of [yus988/pingpong-music_genres_classification-finetuned](https://huggingface.co/yus988/pingpong-music_genres_classification-finetuned) on the GTZAN dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2967
+- Accuracy: 0.94
+
+## 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: 1
+- eval_batch_size: 1
+- seed: 42
+- gradient_accumulation_steps: 8
+- 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: 7
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.4316        | 1.0   | 112  | 1.2668          | 0.75     |
+| 1.7743        | 1.99  | 224  | 1.0659          | 0.64     |
+| 0.9712        | 3.0   | 337  | 0.5958          | 0.84     |
+| 1.2043        | 4.0   | 449  | 0.6563          | 0.86     |
+| 0.5506        | 4.99  | 561  | 0.3875          | 0.9      |
+| 0.5882        | 6.0   | 674  | 0.4775          | 0.9      |
+| 0.3522        | 6.98  | 784  | 0.2967          | 0.94     |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.0