---
library_name: transformers
license: apache-2.0
base_model: yojul/wav2vec2-base-one-shot-hip-hop-drums-clf
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: wav2vec2-base-one-shot-hip-hop-drums-clf-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: 0.74
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# wav2vec2-base-one-shot-hip-hop-drums-clf-finetuned-gtzan

This model is a fine-tuned version of [yojul/wav2vec2-base-one-shot-hip-hop-drums-clf](https://huggingface.co./yojul/wav2vec2-base-one-shot-hip-hop-drums-clf) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9288
- Accuracy: 0.74

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7695        | 1.0   | 100  | 1.9632          | 0.345    |
| 1.3851        | 2.0   | 200  | 1.3526          | 0.56     |
| 1.0214        | 3.0   | 300  | 1.3209          | 0.58     |
| 0.725         | 4.0   | 400  | 1.0294          | 0.72     |
| 0.6425        | 5.0   | 500  | 0.9288          | 0.74     |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1