---
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: hubert-classifier
  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-classifier

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: 3.9330
- Accuracy: 0.0674
- Precision: 0.0116
- Recall: 0.0674
- F1: 0.0182
- Binary: 0.3423

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Binary |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
| No log        | 0.96  | 50   | 4.4099          | 0.0647   | 0.0191    | 0.0647 | 0.0221 | 0.2396 |
| No log        | 1.91  | 100  | 4.3523          | 0.0593   | 0.0190    | 0.0593 | 0.0194 | 0.3019 |
| No log        | 2.87  | 150  | 4.2416          | 0.0701   | 0.0246    | 0.0701 | 0.0235 | 0.3358 |
| No log        | 3.83  | 200  | 4.1412          | 0.0701   | 0.0265    | 0.0701 | 0.0214 | 0.3437 |
| No log        | 4.78  | 250  | 4.0716          | 0.0593   | 0.0069    | 0.0593 | 0.0122 | 0.3334 |
| No log        | 5.74  | 300  | 4.0195          | 0.0701   | 0.0124    | 0.0701 | 0.0186 | 0.3453 |
| No log        | 6.7   | 350  | 3.9850          | 0.0593   | 0.0073    | 0.0593 | 0.0126 | 0.3350 |
| No log        | 7.66  | 400  | 3.9610          | 0.0647   | 0.0097    | 0.0647 | 0.0162 | 0.3388 |
| No log        | 8.61  | 450  | 3.9420          | 0.0674   | 0.0113    | 0.0674 | 0.0180 | 0.3396 |
| 4.2019        | 9.57  | 500  | 3.9330          | 0.0674   | 0.0116    | 0.0674 | 0.0182 | 0.3423 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.15.1