---
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
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: 0.6376
- 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: 4
- eval_batch_size: 4
- 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7703        | 1.0   | 225  | 1.6440          | 0.45     |
| 0.9968        | 2.0   | 450  | 1.1709          | 0.6      |
| 0.3874        | 3.0   | 675  | 0.7769          | 0.77     |
| 0.8894        | 4.0   | 900  | 0.5280          | 0.84     |
| 0.1964        | 5.0   | 1125 | 0.6280          | 0.84     |
| 0.2273        | 6.0   | 1350 | 0.6823          | 0.82     |
| 0.0686        | 7.0   | 1575 | 0.6527          | 0.85     |
| 0.1212        | 8.0   | 1800 | 0.5111          | 0.86     |
| 0.014         | 9.0   | 2025 | 0.5715          | 0.86     |
| 0.012         | 10.0  | 2250 | 0.6376          | 0.85     |


### Framework versions

- Transformers 4.39.2
- Pytorch 1.13.0+cu117
- Datasets 2.16.1
- Tokenizers 0.15.1