metadata
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- gtzan
metrics:
- accuracy
model-index:
- name: wav2vec2-base-finetuned-gtzan
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: gtzan
type: 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: 0.9600
- 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 |
|---|---|---|---|---|
| 2.2696 | 0.99 | 28 | 2.1350 | 0.45 |
| 1.9724 | 1.98 | 56 | 1.7939 | 0.63 |
| 1.7172 | 2.97 | 84 | 1.6356 | 0.58 |
| 1.5428 | 4.0 | 113 | 1.4019 | 0.71 |
| 1.3184 | 4.99 | 141 | 1.3236 | 0.73 |
| 1.2897 | 5.98 | 169 | 1.1980 | 0.79 |
| 1.1657 | 6.97 | 197 | 1.0928 | 0.84 |
| 1.0407 | 8.0 | 226 | 1.0616 | 0.83 |
| 0.9717 | 8.99 | 254 | 0.9931 | 0.87 |
| 0.9158 | 9.91 | 280 | 0.9600 | 0.85 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1