metadata
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: hubert-base-ls960-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: 0.82
hubert-base-ls960-finetuned-gtzan
This model is a fine-tuned version of facebook/hubert-base-ls960 on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 0.6905
- 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- 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 |
|---|---|---|---|---|
| 2.1336 | 1.0 | 56 | 2.0042 | 0.29 |
| 1.8196 | 1.99 | 112 | 1.6866 | 0.46 |
| 1.646 | 2.99 | 168 | 1.4015 | 0.58 |
| 1.2508 | 4.0 | 225 | 1.1711 | 0.68 |
| 1.0361 | 5.0 | 281 | 0.9617 | 0.75 |
| 1.0859 | 5.99 | 337 | 1.0006 | 0.68 |
| 1.0419 | 6.99 | 393 | 0.8231 | 0.76 |
| 0.9032 | 8.0 | 450 | 0.7446 | 0.83 |
| 0.6317 | 9.0 | 506 | 0.6654 | 0.85 |
| 0.6474 | 9.96 | 560 | 0.6905 | 0.82 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3