---
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: 0.775
---

<!-- 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 [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2754
- Accuracy: 0.775

## 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: 12
- eval_batch_size: 12
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2856        | 1.0   | 67   | 2.2801          | 0.19     |
| 2.1936        | 2.0   | 134  | 2.1829          | 0.335    |
| 1.9496        | 3.0   | 201  | 1.9189          | 0.5      |
| 1.6727        | 4.0   | 268  | 1.6280          | 0.595    |
| 1.5444        | 5.0   | 335  | 1.4530          | 0.635    |
| 1.0974        | 6.0   | 402  | 1.2269          | 0.67     |
| 1.0647        | 7.0   | 469  | 1.0802          | 0.72     |
| 0.8521        | 8.0   | 536  | 0.9819          | 0.72     |
| 0.7618        | 9.0   | 603  | 0.9660          | 0.74     |
| 0.5022        | 10.0  | 670  | 0.8664          | 0.75     |
| 0.4576        | 11.0  | 737  | 0.8972          | 0.7      |
| 0.2801        | 12.0  | 804  | 0.8073          | 0.76     |
| 0.2404        | 13.0  | 871  | 0.7892          | 0.765    |
| 0.1493        | 14.0  | 938  | 0.8512          | 0.74     |
| 0.0945        | 15.0  | 1005 | 0.8876          | 0.74     |
| 0.049         | 16.0  | 1072 | 0.9735          | 0.72     |
| 0.0311        | 17.0  | 1139 | 0.9881          | 0.76     |
| 0.0225        | 18.0  | 1206 | 1.0965          | 0.735    |
| 0.0164        | 19.0  | 1273 | 1.0578          | 0.76     |
| 0.0124        | 20.0  | 1340 | 1.0298          | 0.75     |
| 0.0109        | 21.0  | 1407 | 1.0762          | 0.745    |
| 0.0085        | 22.0  | 1474 | 1.1168          | 0.75     |
| 0.0071        | 23.0  | 1541 | 1.1697          | 0.73     |
| 0.0063        | 24.0  | 1608 | 1.1204          | 0.765    |
| 0.0054        | 25.0  | 1675 | 1.1270          | 0.765    |
| 0.005         | 26.0  | 1742 | 1.1315          | 0.76     |
| 0.0521        | 27.0  | 1809 | 1.1868          | 0.755    |
| 0.004         | 28.0  | 1876 | 1.1645          | 0.77     |
| 0.0468        | 29.0  | 1943 | 1.1515          | 0.775    |
| 0.0036        | 30.0  | 2010 | 1.1655          | 0.775    |
| 0.0595        | 31.0  | 2077 | 1.2069          | 0.76     |
| 0.003         | 32.0  | 2144 | 1.2012          | 0.77     |
| 0.0029        | 33.0  | 2211 | 1.2369          | 0.755    |
| 0.0027        | 34.0  | 2278 | 1.2397          | 0.765    |
| 0.0026        | 35.0  | 2345 | 1.2581          | 0.765    |
| 0.029         | 36.0  | 2412 | 1.2226          | 0.76     |
| 0.0024        | 37.0  | 2479 | 1.1833          | 0.775    |
| 0.0023        | 38.0  | 2546 | 1.2723          | 0.765    |
| 0.0023        | 39.0  | 2613 | 1.2575          | 0.77     |
| 0.0284        | 40.0  | 2680 | 1.2945          | 0.76     |
| 0.002         | 41.0  | 2747 | 1.2345          | 0.765    |
| 0.0203        | 42.0  | 2814 | 1.2607          | 0.77     |
| 0.002         | 43.0  | 2881 | 1.2945          | 0.765    |
| 0.0019        | 44.0  | 2948 | 1.2487          | 0.77     |
| 0.0018        | 45.0  | 3015 | 1.2626          | 0.78     |
| 0.0018        | 46.0  | 3082 | 1.2692          | 0.77     |
| 0.0017        | 47.0  | 3149 | 1.2783          | 0.77     |
| 0.0018        | 48.0  | 3216 | 1.2813          | 0.775    |
| 0.0017        | 49.0  | 3283 | 1.2861          | 0.775    |
| 0.0275        | 50.0  | 3350 | 1.2754          | 0.775    |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0