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: 0.6912
- 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.0279 | 1.0 | 112 | 2.1237 | 0.14 |
| 1.8601 | 1.99 | 224 | 1.4994 | 0.55 |
| 1.2448 | 3.0 | 337 | 1.2065 | 0.62 |
| 1.2081 | 4.0 | 449 | 0.9849 | 0.64 |
| 1.1896 | 4.99 | 561 | 0.8475 | 0.69 |
| 0.6236 | 6.0 | 674 | 1.0019 | 0.73 |
| 0.6113 | 6.99 | 786 | 1.0411 | 0.7 |
| 0.5026 | 8.0 | 899 | 0.8096 | 0.77 |
| 0.5218 | 9.0 | 1011 | 0.7381 | 0.79 |
| 0.4961 | 9.97 | 1120 | 0.6912 | 0.82 |
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0