metadata
library_name: transformers
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: 0.6653
- 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.931 | 0.9956 | 112 | 1.8442 | 0.38 |
| 1.4533 | 2.0 | 225 | 1.4234 | 0.56 |
| 1.5759 | 2.9956 | 337 | 1.3121 | 0.58 |
| 0.9118 | 4.0 | 450 | 1.1423 | 0.68 |
| 0.9785 | 4.9956 | 562 | 0.9830 | 0.71 |
| 0.7014 | 6.0 | 675 | 0.8055 | 0.8 |
| 0.5983 | 6.9956 | 787 | 0.7071 | 0.76 |
| 0.3568 | 8.0 | 900 | 0.7417 | 0.77 |
| 0.4118 | 8.9956 | 1012 | 0.5920 | 0.83 |
| 0.4934 | 9.9556 | 1120 | 0.6653 | 0.82 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3