---
library_name: transformers
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- generated_from_trainer
datasets:
- gtzan
model-index:
- name: hubert-model-v1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# hubert-model-v1

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:
- eval_loss: 2.1979
- eval_accuracy: 0.245
- eval_precision: 0.2882
- eval_recall: 0.245
- eval_f1: 0.1828
- eval_runtime: 105.666
- eval_samples_per_second: 1.893
- eval_steps_per_second: 0.473
- epoch: 1.0
- step: 25

## 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
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0