---
library_name: transformers
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: hubert-base-ls960-finetuned-bmd-V1-20241110_103816-LOSO-section-out4
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# hubert-base-ls960-finetuned-bmd-V1-20241110_103816-LOSO-section-out4

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: 0.8940
- Accuracy: 0.5667
- F1: 0.5472

## 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: 8
- eval_batch_size: 8
- seed: 1968
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use 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     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| No log        | 0.9333 | 7    | 1.0900          | 0.4      | 0.2628 |
| 1.1061        | 2.0    | 15   | 1.0551          | 0.4      | 0.2628 |
| 1.0768        | 2.9333 | 22   | 1.0304          | 0.5333   | 0.4540 |
| 1.0176        | 4.0    | 30   | 0.9738          | 0.4667   | 0.3599 |
| 1.0176        | 4.9333 | 37   | 0.8938          | 0.5333   | 0.4538 |
| 0.9959        | 6.0    | 45   | 0.8884          | 0.5333   | 0.4852 |
| 0.9677        | 6.9333 | 52   | 0.8874          | 0.6333   | 0.5708 |
| 0.7597        | 8.0    | 60   | 0.8811          | 0.6667   | 0.6629 |
| 0.7597        | 8.9333 | 67   | 0.8911          | 0.6      | 0.5761 |
| 0.7455        | 9.3333 | 70   | 0.8940          | 0.5667   | 0.5472 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3