---
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: 1.1326
- Accuracy: 0.86

## 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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0942        | 1.0   | 225  | 1.9649          | 0.33     |
| 1.1113        | 2.0   | 450  | 1.2162          | 0.74     |
| 0.7961        | 3.0   | 675  | 0.9466          | 0.7      |
| 0.9005        | 4.0   | 900  | 0.6644          | 0.83     |
| 0.3228        | 5.0   | 1125 | 0.5374          | 0.85     |
| 0.4422        | 6.0   | 1350 | 0.7370          | 0.76     |
| 0.1283        | 7.0   | 1575 | 0.7234          | 0.84     |
| 0.0076        | 8.0   | 1800 | 0.8727          | 0.85     |
| 0.0037        | 9.0   | 2025 | 0.9373          | 0.84     |
| 0.1723        | 10.0  | 2250 | 0.9524          | 0.86     |
| 0.0016        | 11.0  | 2475 | 1.0349          | 0.84     |
| 0.0016        | 12.0  | 2700 | 1.0471          | 0.85     |
| 0.0011        | 13.0  | 2925 | 1.0802          | 0.85     |
| 0.0009        | 14.0  | 3150 | 1.0722          | 0.85     |
| 0.0007        | 15.0  | 3375 | 1.0931          | 0.85     |
| 0.0007        | 16.0  | 3600 | 1.1442          | 0.85     |
| 0.0007        | 17.0  | 3825 | 1.1239          | 0.85     |
| 0.0005        | 18.0  | 4050 | 1.1810          | 0.85     |
| 0.0006        | 19.0  | 4275 | 1.1560          | 0.85     |
| 0.0005        | 20.0  | 4500 | 1.1326          | 0.86     |


### Framework versions

- Transformers 4.29.2
- Pytorch 1.13.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3