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wav2vec2-xlsr-finetuned-gtzan
spellingdragon/wav2vec2-xlsr-finetuned-gtzan
wav2vec2-xlsr-finetuned-gtzan is a machine learning model from spellingdragon. 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 transformers. 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
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Jan 7, 2024
- Updated
- Jan 14, 2024
- SHA
- 677cc947
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. -->
wav2vec2-xlsr-finetuned-gtzan
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: 0.4910
- Accuracy: 0.88
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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- 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: 8
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.1164 | 1.0 | 112 | 1.8109 | 0.41 |
| 1.4074 | 2.0 | 225 | 1.3693 | 0.52 |
| 1.3318 | 3.0 | 337 | 1.0215 | 0.67 |
| 0.753 | 4.0 | 450 | 0.7795 | 0.76 |
| 0.6883 | 5.0 | 562 | 0.7275 | 0.8 |
| 0.3683 | 6.0 | 675 | 0.5863 | 0.82 |
| 0.2497 | 7.0 | 787 | 0.4621 | 0.89 |
| 0.4483 | 7.96 | 896 | 0.4910 | 0.88 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Jan 7, 2024
- Updated
- Jan 14, 2024