---
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: mert-base-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. -->

# mert-base-finetuned-gtzan

This model is a fine-tuned version of [yangwang825/mert-base](https://huggingface.co/yangwang825/mert-base) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6800
- 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: 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0961        | 1.0   | 112  | 1.2710          | 0.59     |
| 0.9162        | 2.0   | 224  | 1.0297          | 0.64     |
| 0.721         | 3.0   | 336  | 1.1227          | 0.56     |
| 0.5045        | 4.0   | 448  | 0.5215          | 0.83     |
| 0.3727        | 5.0   | 560  | 0.5263          | 0.86     |
| 0.1159        | 6.0   | 672  | 0.8055          | 0.84     |
| 0.0276        | 7.0   | 784  | 0.5396          | 0.87     |
| 0.1           | 8.0   | 896  | 0.6800          | 0.88     |
| 0.2564        | 9.0   | 1008 | 0.5907          | 0.87     |
| 0.1327        | 10.0  | 1120 | 0.5915          | 0.88     |


### Framework versions

- Transformers 4.25.1
- Pytorch 2.5.0+cu121
- Datasets 2.7.1
- Tokenizers 0.13.3