|
--- |
|
library_name: transformers |
|
base_model: leamac51 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- marsyas/gtzan |
|
metrics: |
|
- accuracy |
|
- f1 |
|
model-index: |
|
- name: bsclass-finetuned-gtzan-1st-aprox-less-LR |
|
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: 0.915 |
|
- name: F1 |
|
type: f1 |
|
value: 0.9147312393158322 |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# bsclass-finetuned-gtzan-1st-aprox-less-LR |
|
|
|
This model is a fine-tuned version of [leamac51](https://huggingface.co/leamac51) on the GTZAN dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.5240 |
|
- Accuracy: 0.915 |
|
- F1: 0.9147 |
|
|
|
## 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: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Use OptimizerNames.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 | F1 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
|
| 2.0897 | 1.0 | 100 | 2.0161 | 0.685 | 0.6827 | |
|
| 1.6456 | 2.0 | 200 | 1.7330 | 0.66 | 0.6290 | |
|
| 1.4091 | 3.0 | 300 | 1.3255 | 0.78 | 0.7732 | |
|
| 1.1217 | 4.0 | 400 | 1.1425 | 0.82 | 0.8186 | |
|
| 1.0118 | 5.0 | 500 | 0.9657 | 0.85 | 0.8524 | |
|
| 0.7186 | 6.0 | 600 | 0.7777 | 0.86 | 0.8609 | |
|
| 0.4308 | 7.0 | 700 | 0.5975 | 0.905 | 0.9040 | |
|
| 0.451 | 8.0 | 800 | 0.5240 | 0.915 | 0.9147 | |
|
| 0.3558 | 9.0 | 900 | 0.5822 | 0.885 | 0.8853 | |
|
| 0.2556 | 10.0 | 1000 | 0.5207 | 0.905 | 0.9052 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.48.3 |
|
- Pytorch 2.5.1+cu124 |
|
- Datasets 3.3.2 |
|
- Tokenizers 0.21.0 |
|
|
