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distilhubert-audio-course-finetuned-gtzan-v5

Audio Classification
Transformers
PyTorch
hubert
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
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README.md ADDED
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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-audio-course-finetuned-gtzan-v5
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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: 0.87
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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-audio-course-finetuned-gtzan-v5
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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: 0.9236
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+ - Accuracy: 0.87
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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: 0.0001
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 16
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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: 0.7
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+ - num_epochs: 50
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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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+ | 2.2989 | 0.99 | 56 | 2.2882 | 0.11 |
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+ | 2.2716 | 2.0 | 113 | 2.2469 | 0.31 |
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+ | 2.1919 | 2.99 | 169 | 2.1317 | 0.4 |
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+ | 2.0117 | 4.0 | 226 | 1.9244 | 0.53 |
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+ | 1.7966 | 4.99 | 282 | 1.7315 | 0.65 |
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+ | 1.6379 | 6.0 | 339 | 1.5920 | 0.59 |
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+ | 1.4496 | 6.99 | 395 | 1.3539 | 0.71 |
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+ | 1.3264 | 8.0 | 452 | 1.1879 | 0.7 |
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+ | 1.0601 | 8.99 | 508 | 1.1342 | 0.7 |
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+ | 0.9737 | 10.0 | 565 | 0.9209 | 0.79 |
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+ | 0.7915 | 10.99 | 621 | 0.8768 | 0.74 |
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+ | 0.6432 | 12.0 | 678 | 0.8060 | 0.8 |
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+ | 0.5217 | 12.99 | 734 | 0.6562 | 0.85 |
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+ | 0.3335 | 14.0 | 791 | 0.7744 | 0.76 |
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+ | 0.2866 | 14.99 | 847 | 0.6969 | 0.82 |
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+ | 0.1425 | 16.0 | 904 | 0.6378 | 0.82 |
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+ | 0.1278 | 16.99 | 960 | 0.6972 | 0.82 |
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+ | 0.0706 | 18.0 | 1017 | 0.7328 | 0.84 |
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+ | 0.0301 | 18.99 | 1073 | 0.9245 | 0.76 |
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+ | 0.0379 | 20.0 | 1130 | 0.8437 | 0.85 |
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+ | 0.0147 | 20.99 | 1186 | 0.7489 | 0.83 |
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+ | 0.0067 | 22.0 | 1243 | 0.8975 | 0.83 |
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+ | 0.0049 | 22.99 | 1299 | 1.1788 | 0.81 |
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+ | 0.0038 | 24.0 | 1356 | 1.1146 | 0.81 |
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+ | 0.0028 | 24.99 | 1412 | 1.0270 | 0.85 |
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+ | 0.0027 | 26.0 | 1469 | 1.0634 | 0.83 |
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+ | 0.0024 | 26.99 | 1525 | 1.0220 | 0.84 |
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+ | 0.0023 | 28.0 | 1582 | 1.0282 | 0.83 |
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+ | 0.0487 | 28.99 | 1638 | 1.0735 | 0.82 |
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+ | 0.0458 | 30.0 | 1695 | 1.1198 | 0.82 |
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+ | 0.2453 | 30.99 | 1751 | 1.1154 | 0.81 |
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+ | 0.0552 | 32.0 | 1808 | 1.1630 | 0.79 |
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+ | 0.1202 | 32.99 | 1864 | 1.2746 | 0.81 |
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+ | 0.2709 | 34.0 | 1921 | 1.3797 | 0.79 |
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+ | 0.275 | 34.99 | 1977 | 1.5372 | 0.75 |
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+ | 0.1268 | 36.0 | 2034 | 0.8140 | 0.86 |
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+ | 0.1582 | 36.99 | 2090 | 1.4153 | 0.77 |
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+ | 0.0054 | 38.0 | 2147 | 1.3796 | 0.79 |
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+ | 0.0299 | 38.99 | 2203 | 1.3653 | 0.78 |
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+ | 0.0199 | 40.0 | 2260 | 0.9987 | 0.87 |
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+ | 0.0021 | 40.99 | 2316 | 1.0689 | 0.84 |
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+ | 0.0007 | 42.0 | 2373 | 1.0383 | 0.85 |
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+ | 0.0006 | 42.99 | 2429 | 1.0493 | 0.84 |
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+ | 0.0006 | 44.0 | 2486 | 1.0744 | 0.85 |
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+ | 0.0005 | 44.99 | 2542 | 0.9151 | 0.86 |
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+ | 0.0004 | 46.0 | 2599 | 0.8946 | 0.87 |
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+ | 0.01 | 46.99 | 2655 | 0.8960 | 0.88 |
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+ | 0.0073 | 48.0 | 2712 | 0.9485 | 0.87 |
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+ | 0.0004 | 48.99 | 2768 | 0.9247 | 0.87 |
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+ | 0.0004 | 49.56 | 2800 | 0.9236 | 0.87 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.32.1
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.14.4
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+ - Tokenizers 0.13.3
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