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: 0.88
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: 0.7650
- Accuracy: 0.88
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.2258 | 1.0 | 225 | 1.9240 | 0.28 |
| 1.6083 | 2.0 | 450 | 1.4887 | 0.39 |
| 1.3983 | 3.0 | 675 | 1.3524 | 0.56 |
| 0.7368 | 4.0 | 900 | 1.3110 | 0.56 |
| 0.6121 | 5.0 | 1125 | 0.9572 | 0.72 |
| 0.1772 | 6.0 | 1350 | 0.8775 | 0.73 |
| 1.8666 | 7.0 | 1575 | 0.6078 | 0.82 |
| 0.091 | 8.0 | 1800 | 0.9999 | 0.76 |
| 0.0458 | 9.0 | 2025 | 0.7169 | 0.83 |
| 0.6817 | 10.0 | 2250 | 0.7614 | 0.86 |
| 0.7023 | 11.0 | 2475 | 0.9348 | 0.84 |
| 0.0047 | 12.0 | 2700 | 0.7222 | 0.88 |
| 0.0363 | 13.0 | 2925 | 0.7027 | 0.89 |
| 0.0073 | 14.0 | 3150 | 0.7440 | 0.88 |
| 0.0055 | 15.0 | 3375 | 0.7650 | 0.88 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0