transformers pytorch tensorboard safetensors hubert audio-classification generated_from_trainer dataset:marsyas/gtzan base_model:ntu-spml/distilhubert license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: ntu-spml/distilhubert
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: 0.87
---

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# distilhubert-finetuned-gtzan

This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0924
- Accuracy: 0.87

## 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: 2
- eval_batch_size: 2
- seed: 42
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7495        | 1.0   | 450  | 1.7168          | 0.52     |
| 1.1633        | 2.0   | 900  | 1.0515          | 0.66     |
| 0.3792        | 3.0   | 1350 | 0.7312          | 0.73     |
| 0.5365        | 4.0   | 1800 | 0.9707          | 0.75     |
| 0.0234        | 5.0   | 2250 | 1.1124          | 0.75     |
| 0.0039        | 6.0   | 2700 | 0.9717          | 0.82     |
| 0.1781        | 7.0   | 3150 | 1.0491          | 0.82     |
| 0.0009        | 8.0   | 3600 | 1.1946          | 0.83     |
| 0.0007        | 9.0   | 4050 | 1.1116          | 0.84     |
| 0.0004        | 10.0  | 4500 | 1.0814          | 0.85     |
| 0.0004        | 11.0  | 4950 | 1.1160          | 0.85     |
| 0.0003        | 12.0  | 5400 | 1.1082          | 0.85     |
| 0.0003        | 13.0  | 5850 | 1.1311          | 0.86     |
| 0.0002        | 14.0  | 6300 | 1.1159          | 0.86     |
| 0.0003        | 15.0  | 6750 | 1.0924          | 0.87     |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
