leo-kwan
/

wav2vec2-base-100k-gtzan-music-genres-finetuned-gtzan

@@ -1,199 +1,87 @@
 ---
-library_name: transformers
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-# Model Card for Model ID
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 ---
+base_model: m3hrdadfi/wav2vec2-base-100k-gtzan-music-genres
+tags:
+- generated_from_trainer
+datasets:
+- marsyas/gtzan
+metrics:
+- accuracy
+model-index:
+- name: wav2vec2-base-100k-gtzan-music-genres-finetuned-gtzan
+  results:
+  - task:
+      name: Audio Classification
+      type: audio-classification
+    dataset:
+      name: GTZAN
+      type: marsyas/gtzan
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.98
 ---
+<!-- 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. -->
+# wav2vec2-base-100k-gtzan-music-genres-finetuned-gtzan
+This model is a fine-tuned version of [m3hrdadfi/wav2vec2-base-100k-gtzan-music-genres](https://huggingface.co/m3hrdadfi/wav2vec2-base-100k-gtzan-music-genres) on the GTZAN dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6843
+- Accuracy: 0.98
+## 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: 8
+- total_train_batch_size: 16
+- 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 |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 2.1932        | 0.9976 | 53   | 2.1037          | 0.82     |
+| 1.9212        | 1.9953 | 106  | 1.8040          | 0.8267   |
+| 1.6379        | 2.9929 | 159  | 1.5650          | 0.8667   |
+| 1.4604        | 3.9906 | 212  | 1.3201          | 0.9267   |
+| 1.2249        | 4.9882 | 265  | 1.1253          | 0.94     |
+| 1.075         | 5.9859 | 318  | 0.9814          | 0.96     |
+| 0.911         | 6.9835 | 371  | 0.8447          | 0.9667   |
+| 0.852         | 8.0    | 425  | 0.7628          | 0.9667   |
+| 0.7625        | 8.9976 | 478  | 0.7117          | 0.9733   |
+| 0.7099        | 9.9765 | 530  | 0.6843          | 0.98     |
+### Framework versions
+- Transformers 4.40.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1