---
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: distilhubert-new-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: 0.85
---

<!-- 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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/naganithin2004/huggingface/runs/i8in1y3p)
# distilhubert-new-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: 1.7615
- Accuracy: 0.85

## 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: 16
- eval_batch_size: 16
- 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: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2914        | 1.0   | 57   | 2.2595          | 0.25     |
| 2.1225        | 2.0   | 114  | 2.0265          | 0.57     |
| 1.7631        | 3.0   | 171  | 1.6482          | 0.59     |
| 1.3445        | 4.0   | 228  | 1.3380          | 0.62     |
| 1.1548        | 5.0   | 285  | 1.0589          | 0.72     |
| 0.9289        | 6.0   | 342  | 0.8541          | 0.76     |
| 0.708         | 7.0   | 399  | 0.7628          | 0.79     |
| 0.4497        | 8.0   | 456  | 0.7088          | 0.82     |
| 0.4061        | 9.0   | 513  | 0.6118          | 0.85     |
| 0.286         | 10.0  | 570  | 0.6684          | 0.79     |
| 0.1739        | 11.0  | 627  | 0.5965          | 0.83     |
| 0.1103        | 12.0  | 684  | 0.8414          | 0.81     |
| 0.0922        | 13.0  | 741  | 0.5937          | 0.87     |
| 0.0166        | 14.0  | 798  | 0.5786          | 0.86     |
| 0.0075        | 15.0  | 855  | 0.7950          | 0.84     |
| 0.0014        | 16.0  | 912  | 0.8492          | 0.87     |
| 0.0006        | 17.0  | 969  | 1.2642          | 0.82     |
| 0.0815        | 18.0  | 1026 | 1.1173          | 0.87     |
| 0.0           | 19.0  | 1083 | 1.2181          | 0.86     |
| 0.0           | 20.0  | 1140 | 1.6673          | 0.85     |
| 0.0           | 21.0  | 1197 | 1.4749          | 0.86     |
| 0.0611        | 22.0  | 1254 | 2.2533          | 0.82     |
| 0.0978        | 23.0  | 1311 | 2.0092          | 0.86     |
| 0.0           | 24.0  | 1368 | 2.3586          | 0.83     |
| 0.0           | 25.0  | 1425 | 1.7617          | 0.86     |
| 0.0           | 26.0  | 1482 | 1.7425          | 0.86     |
| 0.0           | 27.0  | 1539 | 1.8418          | 0.85     |
| 0.0           | 28.0  | 1596 | 1.6987          | 0.87     |
| 0.0           | 29.0  | 1653 | 1.9399          | 0.85     |
| 0.0           | 30.0  | 1710 | 2.4230          | 0.81     |
| 0.0           | 31.0  | 1767 | 1.4312          | 0.88     |
| 0.1807        | 32.0  | 1824 | 1.5278          | 0.87     |
| 0.0           | 33.0  | 1881 | 1.3795          | 0.88     |
| 0.0           | 34.0  | 1938 | 1.5051          | 0.88     |
| 0.0           | 35.0  | 1995 | 1.6587          | 0.85     |
| 0.0           | 36.0  | 2052 | 1.6256          | 0.86     |
| 0.0           | 37.0  | 2109 | 1.7290          | 0.85     |
| 0.0           | 38.0  | 2166 | 1.8676          | 0.87     |
| 0.0           | 39.0  | 2223 | 1.8963          | 0.86     |
| 0.166         | 40.0  | 2280 | 1.7057          | 0.85     |
| 0.1293        | 41.0  | 2337 | 1.4235          | 0.87     |
| 0.1491        | 42.0  | 2394 | 1.7916          | 0.85     |
| 0.1416        | 43.0  | 2451 | 1.8634          | 0.85     |
| 0.0           | 44.0  | 2508 | 1.6286          | 0.86     |
| 0.0526        | 45.0  | 2565 | 1.6242          | 0.86     |
| 0.0           | 46.0  | 2622 | 1.7576          | 0.85     |
| 0.0           | 47.0  | 2679 | 1.7897          | 0.85     |
| 0.0           | 48.0  | 2736 | 1.7571          | 0.85     |
| 0.0018        | 49.0  | 2793 | 1.6993          | 0.85     |
| 0.0           | 50.0  | 2850 | 1.7615          | 0.85     |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1