---
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: wav2vec2-base-960h-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: 0.73
---

<!-- 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-960h-finetuned-gtzan

This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0690
- Accuracy: 0.73

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 2.3011        | 0.9956  | 56   | 2.2915          | 0.1      |
| 2.2365        | 1.9911  | 112  | 2.1198          | 0.37     |
| 1.9162        | 2.9867  | 168  | 1.9024          | 0.42     |
| 1.7154        | 4.0     | 225  | 1.7397          | 0.39     |
| 1.757         | 4.9956  | 281  | 1.5732          | 0.47     |
| 1.546         | 5.9911  | 337  | 1.5172          | 0.47     |
| 1.5738        | 6.9867  | 393  | 1.3950          | 0.54     |
| 1.2893        | 8.0     | 450  | 1.4202          | 0.56     |
| 1.2745        | 8.9956  | 506  | 1.2819          | 0.59     |
| 1.2632        | 9.9911  | 562  | 1.2788          | 0.66     |
| 1.2195        | 10.9867 | 618  | 1.1909          | 0.63     |
| 1.1151        | 12.0    | 675  | 1.1605          | 0.62     |
| 1.0165        | 12.9956 | 731  | 1.1202          | 0.67     |
| 0.9418        | 13.9911 | 787  | 1.0747          | 0.73     |
| 0.9686        | 14.9333 | 840  | 1.0690          | 0.73     |


### Framework versions

- Transformers 4.43.2
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1