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---
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: hubert-base-ls960-v2-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: 0.86
---
<!-- 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. -->
# hubert-base-ls960-v2-finetuned-gtzan
This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6560
- Accuracy: 0.86
## 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: 10
- eval_batch_size: 10
- 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: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1778 | 1.0 | 90 | 2.1185 | 0.42 |
| 1.7477 | 2.0 | 180 | 1.6950 | 0.5 |
| 1.6626 | 3.0 | 270 | 1.4481 | 0.49 |
| 1.0488 | 4.0 | 360 | 1.2952 | 0.56 |
| 0.9819 | 5.0 | 450 | 1.0239 | 0.63 |
| 0.8553 | 6.0 | 540 | 0.8149 | 0.75 |
| 0.9188 | 7.0 | 630 | 0.9471 | 0.73 |
| 0.5563 | 8.0 | 720 | 0.7414 | 0.77 |
| 0.6793 | 9.0 | 810 | 0.7851 | 0.78 |
| 0.5282 | 10.0 | 900 | 0.6163 | 0.8 |
| 0.3895 | 11.0 | 990 | 0.6667 | 0.82 |
| 0.3037 | 12.0 | 1080 | 0.6157 | 0.84 |
| 0.1647 | 13.0 | 1170 | 0.6485 | 0.83 |
| 0.3331 | 14.0 | 1260 | 0.5609 | 0.86 |
| 0.1695 | 15.0 | 1350 | 0.6393 | 0.84 |
| 0.0968 | 16.0 | 1440 | 0.7537 | 0.83 |
| 0.1928 | 17.0 | 1530 | 0.7043 | 0.86 |
| 0.1281 | 18.0 | 1620 | 0.6077 | 0.89 |
| 0.0482 | 19.0 | 1710 | 0.7178 | 0.86 |
| 0.1215 | 20.0 | 1800 | 0.6560 | 0.86 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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