metadata
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: 0.8
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: 0.7670
- Accuracy: 0.8
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: 3e-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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.0554 | 1.0 | 100 | 2.0109 | 0.465 |
| 1.5036 | 2.0 | 200 | 1.5547 | 0.53 |
| 1.348 | 3.0 | 300 | 1.2558 | 0.685 |
| 1.1877 | 4.0 | 400 | 1.1226 | 0.7 |
| 0.8857 | 5.0 | 500 | 0.9978 | 0.76 |
| 0.6167 | 6.0 | 600 | 0.9513 | 0.755 |
| 0.5439 | 7.0 | 700 | 0.8185 | 0.78 |
| 0.5015 | 8.0 | 800 | 0.7880 | 0.815 |
| 0.2221 | 9.0 | 900 | 0.7777 | 0.8 |
| 0.3112 | 10.0 | 1000 | 0.7670 | 0.8 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1