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: 0.86
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: 0.5653
- Accuracy: 0.86
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.9774 | 1.0 | 113 | 1.9927 | 0.28 |
| 1.5184 | 2.0 | 226 | 1.4378 | 0.5 |
| 1.3158 | 3.0 | 339 | 1.1390 | 0.72 |
| 0.8236 | 4.0 | 452 | 1.0595 | 0.69 |
| 0.7644 | 5.0 | 565 | 1.0361 | 0.7 |
| 0.5783 | 6.0 | 678 | 0.6584 | 0.82 |
| 0.4597 | 7.0 | 791 | 0.5901 | 0.87 |
| 0.2232 | 8.0 | 904 | 0.5699 | 0.87 |
| 0.1191 | 9.0 | 1017 | 0.5567 | 0.88 |
| 0.0797 | 10.0 | 1130 | 0.5653 | 0.86 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.1