---
library_name: transformers
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: hubert-custom
  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. -->

# hubert-custom

This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6927
- Accuracy: 0.5156

## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- 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
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.6835        | 2.7778  | 100  | 0.6809          | 0.5625   |
| 0.6998        | 5.5556  | 200  | 0.6928          | 0.5156   |
| 0.711         | 8.3333  | 300  | 0.7050          | 0.4844   |
| 0.6965        | 11.1111 | 400  | 0.6932          | 0.4844   |
| 0.6994        | 13.8889 | 500  | 0.7030          | 0.4844   |
| 0.7002        | 16.6667 | 600  | 0.6927          | 0.5156   |
| 0.6982        | 19.4444 | 700  | 0.6935          | 0.4844   |
| 0.6981        | 22.2222 | 800  | 0.6928          | 0.5156   |
| 0.6942        | 25.0    | 900  | 0.6923          | 0.5156   |
| 0.6951        | 27.7778 | 1000 | 0.6927          | 0.5156   |


### Framework versions

- Transformers 4.51.1
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1