metadata
library_name: transformers
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-gtzan
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: GTZAN
type: marsyas/gtzan
config: all
split: train
args: all
metrics:
- name: Accuracy
type: accuracy
value: 0.1
distilhubert-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: nan
- Accuracy: 0.1
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0 | 1.0 | 113 | nan | 0.1 |
| 0.0 | 2.0 | 226 | nan | 0.1 |
| 0.0 | 3.0 | 339 | nan | 0.1 |
| 0.0 | 4.0 | 452 | nan | 0.1 |
| 0.0 | 5.0 | 565 | nan | 0.1 |
| 0.0 | 6.0 | 678 | nan | 0.1 |
| 0.0 | 7.0 | 791 | nan | 0.1 |
| 0.0 | 8.0 | 904 | nan | 0.1 |
| 0.0 | 9.0 | 1017 | nan | 0.1 |
| 0.0 | 10.0 | 1130 | nan | 0.1 |
| 0.0 | 11.0 | 1243 | nan | 0.1 |
| 0.0 | 12.0 | 1356 | nan | 0.1 |
| 0.0 | 13.0 | 1469 | nan | 0.1 |
| 0.0 | 14.0 | 1582 | nan | 0.1 |
| 0.0 | 15.0 | 1695 | nan | 0.1 |
| 0.0 | 16.0 | 1808 | nan | 0.1 |
| 0.0 | 17.0 | 1921 | nan | 0.1 |
| 0.0 | 18.0 | 2034 | nan | 0.1 |
| 0.0 | 19.0 | 2147 | nan | 0.1 |
| 0.0 | 20.0 | 2260 | nan | 0.1 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1