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

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilhubert-finetuned-gtzan-finetuned-gtzan

This model is a fine-tuned version of [NemesisAlm/distilhubert-finetuned-gtzan](https://huggingface.co/NemesisAlm/distilhubert-finetuned-gtzan) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1781
- Accuracy: 0.79

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.132         | 1.0   | 112  | 2.0618          | 0.75     |
| 0.0004        | 2.0   | 225  | 2.5336          | 0.73     |
| 0.0001        | 3.0   | 337  | 2.0191          | 0.78     |
| 0.0001        | 4.0   | 450  | 2.0529          | 0.79     |
| 0.0           | 4.98  | 560  | 2.1781          | 0.79     |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2