---
library_name: transformers
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: hubert-base-ls960-2clsfinetuned-bmd-V1-20250201_145011-LOSO-section-out5
  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-base-ls960-2clsfinetuned-bmd-V1-20250201_145011-LOSO-section-out5

This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7381
- Accuracy: 0.7273
- F1: 0.7273
- Precision: 0.7273
- Recall: 0.7273

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 1968
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 5    | 0.6674          | 0.5909   | 0.5087 | 0.775     | 0.5909 |
| 0.6794        | 2.0   | 10   | 0.6130          | 0.7727   | 0.7723 | 0.775     | 0.7727 |
| 0.6794        | 3.0   | 15   | 0.6236          | 0.6818   | 0.6645 | 0.7292    | 0.6818 |
| 0.5818        | 4.0   | 20   | 0.6672          | 0.6364   | 0.5810 | 0.7895    | 0.6364 |
| 0.5818        | 5.0   | 25   | 0.5214          | 0.7727   | 0.7723 | 0.775     | 0.7727 |
| 0.49          | 6.0   | 30   | 0.5402          | 0.7273   | 0.7273 | 0.7273    | 0.7273 |
| 0.49          | 7.0   | 35   | 0.7001          | 0.5455   | 0.5089 | 0.5647    | 0.5455 |
| 0.3862        | 8.0   | 40   | 0.5804          | 0.8182   | 0.8167 | 0.8291    | 0.8182 |
| 0.3862        | 9.0   | 45   | 0.6310          | 0.8182   | 0.8167 | 0.8291    | 0.8182 |
| 0.2812        | 10.0  | 50   | 0.7381          | 0.7273   | 0.7273 | 0.7273    | 0.7273 |


### Framework versions

- Transformers 4.48.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0