---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
base_model: ntu-spml/distilhubert
model-index:
- name: CTC-based-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. -->

# CTC-based-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: 0.7057
- 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: 16
- eval_batch_size: 16
- 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0608        | 1.0   | 57   | 2.0361          | 0.43     |
| 1.663         | 2.0   | 114  | 1.5387          | 0.62     |
| 1.2399        | 3.0   | 171  | 1.2074          | 0.68     |
| 1.0662        | 4.0   | 228  | 1.0805          | 0.65     |
| 0.7986        | 5.0   | 285  | 0.8880          | 0.75     |
| 0.7328        | 6.0   | 342  | 0.8037          | 0.74     |
| 0.5891        | 7.0   | 399  | 0.7918          | 0.78     |
| 0.5227        | 8.0   | 456  | 0.7232          | 0.79     |
| 0.5123        | 9.0   | 513  | 0.7138          | 0.78     |
| 0.5578        | 10.0  | 570  | 0.7057          | 0.79     |


### Framework versions

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