metadata
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: wav2vec2-base-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: 0.7866666666666666
wav2vec2-base-finetuned-gtzan
This model is a fine-tuned version of facebook/wav2vec2-base on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 1.2095
- Accuracy: 0.7867
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.0746 | 1.0 | 107 | 1.9697 | 0.46 |
| 1.5843 | 2.0 | 214 | 1.5908 | 0.5067 |
| 1.5982 | 3.0 | 321 | 1.4385 | 0.58 |
| 1.2855 | 4.0 | 428 | 1.3906 | 0.5467 |
| 1.0562 | 5.0 | 535 | 1.0173 | 0.7 |
| 0.8919 | 6.0 | 642 | 0.9564 | 0.6733 |
| 0.7214 | 7.0 | 749 | 0.8906 | 0.7467 |
| 0.7624 | 8.0 | 856 | 0.9580 | 0.7467 |
| 0.3619 | 9.0 | 963 | 1.0685 | 0.7733 |
| 0.3814 | 10.0 | 1070 | 1.1847 | 0.7467 |
| 0.4371 | 11.0 | 1177 | 0.9630 | 0.7867 |
| 0.3186 | 12.0 | 1284 | 0.9635 | 0.82 |
| 0.1474 | 13.0 | 1391 | 1.0021 | 0.8333 |
| 0.0918 | 14.0 | 1498 | 1.4497 | 0.7533 |
| 0.0592 | 15.0 | 1605 | 1.2592 | 0.7733 |
| 0.0084 | 16.0 | 1712 | 1.2656 | 0.7867 |
| 0.0216 | 17.0 | 1819 | 1.2095 | 0.7867 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0