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: 0.66
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: 1.4561
- Accuracy: 0.66
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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
2.2458 | 0.99 | 28 | 2.0258 | 0.38 |
1.8945 | 1.98 | 56 | 1.7438 | 0.47 |
1.6668 | 2.97 | 84 | 1.5996 | 0.53 |
1.5431 | 4.0 | 113 | 1.4844 | 0.69 |
1.3861 | 4.96 | 140 | 1.4561 | 0.66 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.13.3