---
license: apache-2.0
base_model: arshsin/distilhubert-finetuned-gtzan
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: distilhubert-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. -->

# distilhubert-finetuned-gtzan

This model is a fine-tuned version of [arshsin/distilhubert-finetuned-gtzan](https://huggingface.co/arshsin/distilhubert-finetuned-gtzan) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6457
- 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-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0001        | 0.99  | 56   | 1.4113          | 0.84     |
| 0.0001        | 2.0   | 113  | 1.4248          | 0.84     |
| 0.0001        | 2.99  | 169  | 1.4818          | 0.83     |
| 0.0001        | 4.0   | 226  | 1.5228          | 0.83     |
| 0.0001        | 4.99  | 282  | 1.5067          | 0.84     |
| 0.0032        | 6.0   | 339  | 1.5205          | 0.84     |
| 0.0           | 6.99  | 395  | 1.5488          | 0.84     |
| 0.0           | 8.0   | 452  | 1.5890          | 0.84     |
| 0.0           | 8.99  | 508  | 1.6020          | 0.83     |
| 0.0117        | 10.0  | 565  | 1.5945          | 0.84     |
| 0.0           | 10.99 | 621  | 1.6145          | 0.84     |
| 0.0           | 12.0  | 678  | 1.6370          | 0.83     |
| 0.0           | 12.99 | 734  | 1.6396          | 0.84     |
| 0.0           | 14.0  | 791  | 1.6458          | 0.83     |
| 0.0           | 14.87 | 840  | 1.6457          | 0.84     |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.2
- Datasets 2.17.0
- Tokenizers 0.15.1