---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-gtzan
  results: []
---

<!-- 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: 0.6228
- 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: 4e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2841        | 0.98  | 28   | 2.2578          | 0.22     |
| 2.108         | 2.0   | 57   | 2.0031          | 0.55     |
| 1.7117        | 2.98  | 85   | 1.6220          | 0.65     |
| 1.4624        | 4.0   | 114  | 1.4061          | 0.7      |
| 1.2607        | 4.98  | 142  | 1.1969          | 0.69     |
| 1.1162        | 6.0   | 171  | 1.0955          | 0.75     |
| 1.0           | 6.98  | 199  | 0.9670          | 0.78     |
| 0.8864        | 8.0   | 228  | 0.9192          | 0.77     |
| 0.8583        | 8.98  | 256  | 0.8475          | 0.78     |
| 0.8147        | 10.0  | 285  | 0.8214          | 0.77     |
| 0.6572        | 10.98 | 313  | 0.7754          | 0.78     |
| 0.5958        | 12.0  | 342  | 0.7187          | 0.79     |
| 0.4196        | 12.98 | 370  | 0.6732          | 0.83     |
| 0.4515        | 14.0  | 399  | 0.7272          | 0.8      |
| 0.4256        | 14.98 | 427  | 0.6507          | 0.84     |
| 0.3734        | 16.0  | 456  | 0.6587          | 0.83     |
| 0.3541        | 16.98 | 484  | 0.6244          | 0.86     |
| 0.312         | 18.0  | 513  | 0.6363          | 0.84     |
| 0.3287        | 18.98 | 541  | 0.6226          | 0.86     |
| 0.313         | 19.65 | 560  | 0.6228          | 0.85     |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3