---
library_name: transformers
license: apache-2.0
base_model: sanchit-gandhi/distilhubert-finetuned-gtzan
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: Mawaddaa/distilhubert-finetuned-gtzan
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: GTZAN
      type: marsyas/gtzan
      config: all
      split: train
      args: all
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.83
---

<!-- 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. -->

# Mawaddaa/distilhubert-finetuned-gtzan

This model is a fine-tuned version of [sanchit-gandhi/distilhubert-finetuned-gtzan](https://huggingface.co/sanchit-gandhi/distilhubert-finetuned-gtzan) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8145
- Accuracy: 0.83

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9096        | 1.0   | 225  | 1.7239          | 0.49     |
| 1.056         | 2.0   | 450  | 1.1898          | 0.66     |
| 0.5824        | 3.0   | 675  | 0.7905          | 0.74     |
| 0.2286        | 4.0   | 900  | 0.7436          | 0.8      |
| 0.3129        | 5.0   | 1125 | 0.5656          | 0.84     |
| 0.046         | 6.0   | 1350 | 0.6575          | 0.83     |
| 0.1413        | 7.0   | 1575 | 0.6421          | 0.83     |
| 0.0208        | 8.0   | 1800 | 0.8335          | 0.84     |
| 0.0088        | 9.0   | 2025 | 0.8039          | 0.85     |
| 0.0087        | 10.0  | 2250 | 0.8145          | 0.83     |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1