---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-gtzan-v3-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-v3-finetuned-gtzan

This model is a fine-tuned version of [MariaK/distilhubert-finetuned-gtzan-v3](https://huggingface.co/MariaK/distilhubert-finetuned-gtzan-v3) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4764
- Accuracy: 0.88

## 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: 2e-05
- 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: 0.2
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0791        | 0.99  | 56   | 0.5451          | 0.82     |
| 0.0677        | 2.0   | 113  | 0.4793          | 0.88     |
| 0.0329        | 2.97  | 168  | 0.4764          | 0.88     |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3