---
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: distilhubert-audio-course-finetuned-gtzan-v5
  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
---

<!-- 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-audio-course-finetuned-gtzan-v5

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: 0.9236
- 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: 0.0001
- 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: 0.7
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2989        | 0.99  | 56   | 2.2882          | 0.11     |
| 2.2716        | 2.0   | 113  | 2.2469          | 0.31     |
| 2.1919        | 2.99  | 169  | 2.1317          | 0.4      |
| 2.0117        | 4.0   | 226  | 1.9244          | 0.53     |
| 1.7966        | 4.99  | 282  | 1.7315          | 0.65     |
| 1.6379        | 6.0   | 339  | 1.5920          | 0.59     |
| 1.4496        | 6.99  | 395  | 1.3539          | 0.71     |
| 1.3264        | 8.0   | 452  | 1.1879          | 0.7      |
| 1.0601        | 8.99  | 508  | 1.1342          | 0.7      |
| 0.9737        | 10.0  | 565  | 0.9209          | 0.79     |
| 0.7915        | 10.99 | 621  | 0.8768          | 0.74     |
| 0.6432        | 12.0  | 678  | 0.8060          | 0.8      |
| 0.5217        | 12.99 | 734  | 0.6562          | 0.85     |
| 0.3335        | 14.0  | 791  | 0.7744          | 0.76     |
| 0.2866        | 14.99 | 847  | 0.6969          | 0.82     |
| 0.1425        | 16.0  | 904  | 0.6378          | 0.82     |
| 0.1278        | 16.99 | 960  | 0.6972          | 0.82     |
| 0.0706        | 18.0  | 1017 | 0.7328          | 0.84     |
| 0.0301        | 18.99 | 1073 | 0.9245          | 0.76     |
| 0.0379        | 20.0  | 1130 | 0.8437          | 0.85     |
| 0.0147        | 20.99 | 1186 | 0.7489          | 0.83     |
| 0.0067        | 22.0  | 1243 | 0.8975          | 0.83     |
| 0.0049        | 22.99 | 1299 | 1.1788          | 0.81     |
| 0.0038        | 24.0  | 1356 | 1.1146          | 0.81     |
| 0.0028        | 24.99 | 1412 | 1.0270          | 0.85     |
| 0.0027        | 26.0  | 1469 | 1.0634          | 0.83     |
| 0.0024        | 26.99 | 1525 | 1.0220          | 0.84     |
| 0.0023        | 28.0  | 1582 | 1.0282          | 0.83     |
| 0.0487        | 28.99 | 1638 | 1.0735          | 0.82     |
| 0.0458        | 30.0  | 1695 | 1.1198          | 0.82     |
| 0.2453        | 30.99 | 1751 | 1.1154          | 0.81     |
| 0.0552        | 32.0  | 1808 | 1.1630          | 0.79     |
| 0.1202        | 32.99 | 1864 | 1.2746          | 0.81     |
| 0.2709        | 34.0  | 1921 | 1.3797          | 0.79     |
| 0.275         | 34.99 | 1977 | 1.5372          | 0.75     |
| 0.1268        | 36.0  | 2034 | 0.8140          | 0.86     |
| 0.1582        | 36.99 | 2090 | 1.4153          | 0.77     |
| 0.0054        | 38.0  | 2147 | 1.3796          | 0.79     |
| 0.0299        | 38.99 | 2203 | 1.3653          | 0.78     |
| 0.0199        | 40.0  | 2260 | 0.9987          | 0.87     |
| 0.0021        | 40.99 | 2316 | 1.0689          | 0.84     |
| 0.0007        | 42.0  | 2373 | 1.0383          | 0.85     |
| 0.0006        | 42.99 | 2429 | 1.0493          | 0.84     |
| 0.0006        | 44.0  | 2486 | 1.0744          | 0.85     |
| 0.0005        | 44.99 | 2542 | 0.9151          | 0.86     |
| 0.0004        | 46.0  | 2599 | 0.8946          | 0.87     |
| 0.01          | 46.99 | 2655 | 0.8960          | 0.88     |
| 0.0073        | 48.0  | 2712 | 0.9485          | 0.87     |
| 0.0004        | 48.99 | 2768 | 0.9247          | 0.87     |
| 0.0004        | 49.56 | 2800 | 0.9236          | 0.87     |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3