metadata
tags:
- generated_from_trainer
datasets:
- gtzan
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-gtzan
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: gtzan
type: gtzan
config: all
split: train
args: all
metrics:
- name: Accuracy
type: accuracy
value: 0.75
distilhubert-finetuned-gtzan
This model was trained from scratch on the gtzan dataset. It achieves the following results on the evaluation set:
- Accuracy: 0.75
- Loss: 0.7487
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: 8
- 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: 2
Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|---|---|---|---|---|
| 1.9415 | 1.0 | 113 | 0.55 | 1.8500 |
| 1.3078 | 2.0 | 226 | 0.58 | 1.3794 |
| 1.1238 | 3.0 | 339 | 0.65 | 1.0919 |
| 0.788 | 4.0 | 452 | 0.68 | 1.0212 |
| 0.5932 | 5.0 | 565 | 0.69 | 0.8691 |
| 0.4042 | 6.0 | 678 | 0.71 | 0.8527 |
| 0.3421 | 7.0 | 791 | 0.75 | 0.7737 |
| 0.223 | 8.0 | 904 | 0.75 | 0.8463 |
| 0.1162 | 9.0 | 1017 | 0.77 | 0.7808 |
| 0.0863 | 10.0 | 1130 | 0.75 | 0.7487 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.13.2