---
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: 3.2824
- Accuracy: 0.1864
- Precision: 0.1087
- Recall: 0.1864
- F1: 0.1114
- Binary: 0.4189

## 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   | 4.2455          | 0.0533   | 0.0410    | 0.0533 | 0.0255 | 0.3252 |
| No log        | 1.72  | 100  | 3.9851          | 0.0630   | 0.0179    | 0.0630 | 0.0163 | 0.3249 |
| No log        | 2.59  | 150  | 3.7681          | 0.0726   | 0.0401    | 0.0726 | 0.0283 | 0.3421 |
| No log        | 3.45  | 200  | 3.7448          | 0.0678   | 0.0383    | 0.0678 | 0.0252 | 0.3167 |
| No log        | 4.31  | 250  | 3.5775          | 0.0896   | 0.0447    | 0.0896 | 0.0413 | 0.3453 |
| No log        | 5.17  | 300  | 3.5078          | 0.0969   | 0.0380    | 0.0969 | 0.0400 | 0.3482 |
| No log        | 6.03  | 350  | 3.4008          | 0.1283   | 0.0445    | 0.1283 | 0.0587 | 0.3777 |
| No log        | 6.9   | 400  | 3.3443          | 0.1550   | 0.1089    | 0.1550 | 0.0850 | 0.3983 |
| No log        | 7.76  | 450  | 3.2965          | 0.1792   | 0.1052    | 0.1792 | 0.1056 | 0.4177 |
| 3.768         | 8.62  | 500  | 3.2824          | 0.1864   | 0.1087    | 0.1864 | 0.1114 | 0.4189 |
| 3.768         | 9.48  | 550  | 3.2609          | 0.2058   | 0.1339    | 0.2058 | 0.1251 | 0.4332 |


### Framework versions

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