|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- marsyas/gtzan |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: distilhubert-finetuned-gtzan |
|
results: [] |
|
--- |
|
|
|
<!-- 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 |
|
|
|
This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.7339 |
|
- Accuracy: 0.82 |
|
|
|
## 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: 4 |
|
- eval_batch_size: 4 |
|
- seed: 42 |
|
- 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 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 1.9233 | 1.0 | 225 | 1.7014 | 0.49 | |
|
| 0.8822 | 2.0 | 450 | 1.0546 | 0.68 | |
|
| 0.676 | 3.0 | 675 | 0.7165 | 0.78 | |
|
| 0.8326 | 4.0 | 900 | 0.5948 | 0.79 | |
|
| 0.3184 | 5.0 | 1125 | 0.5484 | 0.81 | |
|
| 0.6154 | 6.0 | 1350 | 0.5977 | 0.83 | |
|
| 0.0305 | 7.0 | 1575 | 0.6213 | 0.81 | |
|
| 0.0154 | 8.0 | 1800 | 0.7479 | 0.79 | |
|
| 0.086 | 9.0 | 2025 | 0.6926 | 0.84 | |
|
| 0.0103 | 10.0 | 2250 | 0.7339 | 0.82 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.30.2 |
|
- Pytorch 2.0.0 |
|
- Datasets 2.1.0 |
|
- Tokenizers 0.13.3 |
|
|