metadata
license: apache-2.0
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: 0.84
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: 0.6527
- Accuracy: 0.84
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.1249 | 1.0 | 112 | 1.9377 | 0.43 |
| 1.6556 | 2.0 | 225 | 1.5867 | 0.47 |
| 1.2564 | 3.0 | 337 | 1.2670 | 0.56 |
| 1.0786 | 4.0 | 450 | 1.1080 | 0.59 |
| 0.895 | 5.0 | 562 | 0.8518 | 0.75 |
| 0.7177 | 6.0 | 675 | 1.0047 | 0.7 |
| 0.964 | 7.0 | 787 | 0.7430 | 0.75 |
| 0.4107 | 8.0 | 900 | 1.0347 | 0.71 |
| 0.4166 | 9.0 | 1012 | 0.5399 | 0.85 |
| 0.1234 | 10.0 | 1125 | 0.6266 | 0.83 |
| 0.0902 | 11.0 | 1237 | 0.6292 | 0.84 |
| 0.1211 | 12.0 | 1350 | 0.7393 | 0.84 |
| 0.4082 | 13.0 | 1462 | 0.6524 | 0.85 |
| 0.3442 | 14.0 | 1575 | 0.5732 | 0.86 |
| 0.0913 | 14.93 | 1680 | 0.6527 | 0.84 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.3