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: 0.85
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: 0.6459
- Accuracy: 0.85
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: 2e-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: 11
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.0912 | 1.0 | 113 | 1.9840 | 0.33 |
| 1.7391 | 2.0 | 226 | 1.6205 | 0.57 |
| 1.3242 | 3.0 | 339 | 1.3338 | 0.61 |
| 1.1953 | 4.0 | 452 | 1.1904 | 0.68 |
| 0.8983 | 5.0 | 565 | 1.0357 | 0.75 |
| 0.8686 | 6.0 | 678 | 0.9569 | 0.78 |
| 0.84 | 7.0 | 791 | 0.7681 | 0.8 |
| 0.5776 | 8.0 | 904 | 0.6968 | 0.84 |
| 0.5186 | 9.0 | 1017 | 0.6541 | 0.86 |
| 0.3765 | 10.0 | 1130 | 0.6743 | 0.85 |
| 0.3671 | 11.0 | 1243 | 0.6459 | 0.85 |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3