|
--- |
|
base_model: m3hrdadfi/wav2vec2-base-100k-gtzan-music-genres |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- marsyas/gtzan |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: wav2vec2-base-100k-gtzan-music-genres-finetuned-gtzan |
|
results: |
|
- task: |
|
name: Audio Classification |
|
type: audio-classification |
|
dataset: |
|
name: GTZAN |
|
type: marsyas/gtzan |
|
config: default |
|
split: train |
|
args: default |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.98 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# wav2vec2-base-100k-gtzan-music-genres-finetuned-gtzan |
|
|
|
This model is a fine-tuned version of [m3hrdadfi/wav2vec2-base-100k-gtzan-music-genres](https://huggingface.co/m3hrdadfi/wav2vec2-base-100k-gtzan-music-genres) on the GTZAN dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.6843 |
|
- Accuracy: 0.98 |
|
|
|
## 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: 2 |
|
- eval_batch_size: 2 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 8 |
|
- total_train_batch_size: 16 |
|
- 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 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:------:|:----:|:---------------:|:--------:| |
|
| 2.1932 | 0.9976 | 53 | 2.1037 | 0.82 | |
|
| 1.9212 | 1.9953 | 106 | 1.8040 | 0.8267 | |
|
| 1.6379 | 2.9929 | 159 | 1.5650 | 0.8667 | |
|
| 1.4604 | 3.9906 | 212 | 1.3201 | 0.9267 | |
|
| 1.2249 | 4.9882 | 265 | 1.1253 | 0.94 | |
|
| 1.075 | 5.9859 | 318 | 0.9814 | 0.96 | |
|
| 0.911 | 6.9835 | 371 | 0.8447 | 0.9667 | |
|
| 0.852 | 8.0 | 425 | 0.7628 | 0.9667 | |
|
| 0.7625 | 8.9976 | 478 | 0.7117 | 0.9733 | |
|
| 0.7099 | 9.9765 | 530 | 0.6843 | 0.98 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.40.2 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.19.1 |
|
- Tokenizers 0.19.1 |
|
|
