metadata
license: apache-2.0
base_model: pedromatias97/genre-recognizer-finetuned-gtzan_dset
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: genre-recognizer-finetuned-gtzan_dset-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: 0.94
genre-recognizer-finetuned-gtzan_dset-finetuned-gtzan
This model is a fine-tuned version of pedromatias97/genre-recognizer-finetuned-gtzan_dset on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 0.1555
- Accuracy: 0.94
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: 9e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 39
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.3279 | 0.9956 | 14 | 0.2587 | 0.91 |
0.1625 | 1.9911 | 28 | 0.1822 | 0.95 |
0.1047 | 2.9867 | 42 | 0.1555 | 0.94 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1