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Isaacgv
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distilhubert-finetuned-gtzan

Audio Classification
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hubert
Generated from Trainer
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+ ---
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+ license: apache-2.0
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+ base_model: ntu-spml/distilhubert
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - marsyas/gtzan
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: distilhubert-finetuned-gtzan
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+ results:
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+ - task:
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+ name: Audio Classification
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+ type: audio-classification
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+ dataset:
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+ name: GTZAN
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+ type: marsyas/gtzan
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+ config: all
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+ split: train
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+ args: all
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.86
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # distilhubert-finetuned-gtzan
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+
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+ This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8540
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+ - Accuracy: 0.86
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 30
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 2.2594 | 1.0 | 57 | 2.2216 | 0.37 |
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+ | 1.941 | 2.0 | 114 | 1.8715 | 0.59 |
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+ | 1.4613 | 3.0 | 171 | 1.4244 | 0.65 |
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+ | 1.2449 | 4.0 | 228 | 1.1359 | 0.71 |
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+ | 0.8682 | 5.0 | 285 | 0.9472 | 0.74 |
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+ | 0.6808 | 6.0 | 342 | 0.7817 | 0.78 |
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+ | 0.4759 | 7.0 | 399 | 0.7428 | 0.74 |
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+ | 0.3316 | 8.0 | 456 | 0.6441 | 0.78 |
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+ | 0.2228 | 9.0 | 513 | 0.5838 | 0.83 |
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+ | 0.1367 | 10.0 | 570 | 0.5843 | 0.86 |
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+ | 0.0921 | 11.0 | 627 | 0.5745 | 0.86 |
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+ | 0.0462 | 12.0 | 684 | 0.7029 | 0.83 |
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+ | 0.0513 | 13.0 | 741 | 0.7116 | 0.86 |
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+ | 0.0151 | 14.0 | 798 | 0.7017 | 0.86 |
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+ | 0.0113 | 15.0 | 855 | 0.7439 | 0.85 |
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+ | 0.0572 | 16.0 | 912 | 0.7691 | 0.84 |
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+ | 0.0073 | 17.0 | 969 | 0.7918 | 0.84 |
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+ | 0.0076 | 18.0 | 1026 | 0.8202 | 0.84 |
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+ | 0.0053 | 19.0 | 1083 | 0.8238 | 0.86 |
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+ | 0.0547 | 20.0 | 1140 | 0.8147 | 0.86 |
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+ | 0.0045 | 21.0 | 1197 | 0.8201 | 0.86 |
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+ | 0.004 | 22.0 | 1254 | 0.8282 | 0.83 |
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+ | 0.0038 | 23.0 | 1311 | 0.8387 | 0.86 |
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+ | 0.0035 | 24.0 | 1368 | 0.8398 | 0.86 |
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+ | 0.0033 | 25.0 | 1425 | 0.8403 | 0.86 |
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+ | 0.0031 | 26.0 | 1482 | 0.8464 | 0.86 |
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+ | 0.0032 | 27.0 | 1539 | 0.8456 | 0.86 |
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+ | 0.0031 | 28.0 | 1596 | 0.8505 | 0.86 |
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+ | 0.0031 | 29.0 | 1653 | 0.8517 | 0.86 |
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+ | 0.003 | 30.0 | 1710 | 0.8540 | 0.86 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.31.0
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.0
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+ - Tokenizers 0.13.3