---
library_name: transformers
license: apache-2.0
base_model: yuval6967/wav2vec2-base-finetuned-gtzan
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: wav2vec2-base-finetuned-gtzan-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: 0.83
---

<!-- 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-finetuned-gtzan-finetuned-gtzan

This model is a fine-tuned version of [yuval6967/wav2vec2-base-finetuned-gtzan](https://huggingface.co/yuval6967/wav2vec2-base-finetuned-gtzan) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1628
- Accuracy: 0.83

## 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.2026        | 0.9956 | 112  | 1.2365          | 0.78     |
| 0.3141        | 2.0    | 225  | 1.0698          | 0.8      |
| 0.0457        | 2.9956 | 337  | 0.9390          | 0.84     |
| 0.1295        | 4.0    | 450  | 1.1925          | 0.82     |
| 0.0108        | 4.9956 | 562  | 0.9958          | 0.86     |
| 0.1734        | 6.0    | 675  | 1.5863          | 0.75     |
| 0.0067        | 6.9956 | 787  | 0.9112          | 0.85     |
| 0.2115        | 8.0    | 900  | 1.0695          | 0.83     |
| 0.0061        | 8.9956 | 1012 | 1.1494          | 0.82     |
| 0.0038        | 9.9556 | 1120 | 1.1628          | 0.83     |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1