---
library_name: transformers
license: apache-2.0
base_model: addy88/wav2vec2-base-finetuned-ks
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: wav2vec2-base-finetuned-ks-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: 0.84
---

<!-- 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-ks-finetuned-gtzan

This model is a fine-tuned version of [addy88/wav2vec2-base-finetuned-ks](https://huggingface.co/addy88/wav2vec2-base-finetuned-ks) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6898
- Accuracy: 0.84

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 3.7432        | 1.0    | 113  | 1.8692          | 0.32     |
| 2.5892        | 2.0    | 226  | 1.3959          | 0.55     |
| 2.2446        | 3.0    | 339  | 1.1914          | 0.66     |
| 1.4697        | 4.0    | 452  | 1.1078          | 0.65     |
| 1.1533        | 5.0    | 565  | 0.9681          | 0.72     |
| 1.8984        | 6.0    | 678  | 0.8457          | 0.78     |
| 1.3302        | 7.0    | 791  | 0.9367          | 0.74     |
| 0.5157        | 8.0    | 904  | 0.7358          | 0.83     |
| 0.4856        | 9.0    | 1017 | 0.6366          | 0.83     |
| 0.859         | 9.9156 | 1120 | 0.6898          | 0.84     |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0