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distilhubert-gtzan-loraAL-dropout0.25-split3
MaxLinggg/distilhubert-gtzan-loraAL-dropout0.25-split3
distilhubert-gtzan-loraAL-dropout0.25-split3 is a machine learning model from MaxLinggg. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- May 10, 2025
- Updated
- May 10, 2025
- SHA
- 1754f5c8
Base models
Datasets
Model card
From the Hugging Face model README
<!-- 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. -->
distilhubert-finetuned-gtzan-lora-dropout0.25-split3-full
This model is a fine-tuned version of ntu-spml/distilhubert on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 1.1294
- Accuracy: 0.8433
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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.5075 | 1.0 | 338 | 1.2247 | 0.5067 |
| 1.0213 | 2.0 | 676 | 1.0717 | 0.6333 |
| 0.833 | 3.0 | 1014 | 1.0113 | 0.6667 |
| 0.712 | 4.0 | 1352 | 0.8911 | 0.77 |
| 0.4565 | 5.0 | 1690 | 1.1474 | 0.73 |
| 0.3869 | 6.0 | 2028 | 0.8967 | 0.77 |
| 0.2404 | 7.0 | 2366 | 0.9313 | 0.8233 |
| 0.0816 | 8.0 | 2704 | 1.1234 | 0.83 |
| 0.0499 | 9.0 | 3042 | 1.1998 | 0.8267 |
| 0.0529 | 10.0 | 3380 | 1.1294 | 0.8433 |
Framework versions
- PEFT 0.15.2
- Transformers 4.51.3
- Pytorch 2.6.0
- Datasets 3.3.2
- Tokenizers 0.21.0
- Library
- peft
- License
- apache-2.0
- Created
- May 10, 2025
- Updated
- May 10, 2025