metadata
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: 0.87
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: 0.5690
- Accuracy: 0.87
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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: 25
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.2968 | 1.0 | 57 | 1.2136 | 0.7 |
1.0931 | 2.0 | 114 | 1.1346 | 0.7 |
0.9362 | 3.0 | 171 | 0.9992 | 0.76 |
0.948 | 4.0 | 228 | 0.9344 | 0.76 |
0.7033 | 5.0 | 285 | 0.7802 | 0.81 |
0.6625 | 6.0 | 342 | 0.7777 | 0.79 |
0.5627 | 7.0 | 399 | 0.7143 | 0.81 |
0.5081 | 8.0 | 456 | 0.6232 | 0.86 |
0.4635 | 9.0 | 513 | 0.6564 | 0.85 |
0.3347 | 10.0 | 570 | 0.6108 | 0.85 |
0.2895 | 11.0 | 627 | 0.7139 | 0.8 |
0.2493 | 12.0 | 684 | 0.5887 | 0.84 |
0.2673 | 13.0 | 741 | 0.5907 | 0.86 |
0.1949 | 14.0 | 798 | 0.5798 | 0.83 |
0.1541 | 15.0 | 855 | 0.5532 | 0.87 |
0.1913 | 16.0 | 912 | 0.5314 | 0.87 |
0.1339 | 17.0 | 969 | 0.5337 | 0.88 |
0.0876 | 18.0 | 1026 | 0.5815 | 0.87 |
0.0713 | 19.0 | 1083 | 0.5847 | 0.85 |
0.0869 | 20.0 | 1140 | 0.5456 | 0.86 |
0.0587 | 21.0 | 1197 | 0.5480 | 0.86 |
0.0524 | 22.0 | 1254 | 0.5534 | 0.87 |
0.0621 | 23.0 | 1311 | 0.5707 | 0.87 |
0.0452 | 24.0 | 1368 | 0.5748 | 0.87 |
0.0464 | 25.0 | 1425 | 0.5690 | 0.87 |
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3