---
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: 3.2561
- Accuracy: 0.2155
- Precision: 0.1870
- Recall: 0.2155
- F1: 0.1453
- Binary: 0.4380

## 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: 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        | 0.86  | 50   | 4.2865          | 0.0291   | 0.0034    | 0.0291 | 0.0043 | 0.2661 |
| No log        | 1.72  | 100  | 4.0141          | 0.0460   | 0.0306    | 0.0460 | 0.0187 | 0.3199 |
| No log        | 2.59  | 150  | 3.8172          | 0.0630   | 0.0204    | 0.0630 | 0.0214 | 0.3378 |
| No log        | 3.45  | 200  | 3.7045          | 0.0896   | 0.0534    | 0.0896 | 0.0533 | 0.3431 |
| No log        | 4.31  | 250  | 3.5695          | 0.1308   | 0.0844    | 0.1308 | 0.0796 | 0.3785 |
| No log        | 5.17  | 300  | 3.4883          | 0.1622   | 0.1140    | 0.1622 | 0.1002 | 0.3954 |
| No log        | 6.03  | 350  | 3.4447          | 0.1622   | 0.1145    | 0.1622 | 0.1005 | 0.3925 |
| No log        | 6.9   | 400  | 3.3482          | 0.1671   | 0.0972    | 0.1671 | 0.1026 | 0.4077 |
| No log        | 7.76  | 450  | 3.3042          | 0.1961   | 0.1424    | 0.1961 | 0.1295 | 0.4228 |
| 3.7796        | 8.62  | 500  | 3.2724          | 0.2131   | 0.1898    | 0.2131 | 0.1472 | 0.4370 |
| 3.7796        | 9.48  | 550  | 3.2561          | 0.2155   | 0.1870    | 0.2155 | 0.1453 | 0.4380 |


### Framework versions

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