---
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: 2.6644
- Accuracy: 0.4576
- Precision: 0.4384
- Recall: 0.4576
- F1: 0.3988
- Binary: 0.6165

## 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: 5e-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   | 4.1527          | 0.0484   | 0.0321    | 0.0484 | 0.0218 | 0.3266 |
| No log        | 1.72  | 100  | 3.7623          | 0.0605   | 0.0356    | 0.0605 | 0.0253 | 0.3361 |
| No log        | 2.59  | 150  | 3.5557          | 0.1211   | 0.1031    | 0.1211 | 0.0914 | 0.3731 |
| No log        | 3.45  | 200  | 3.3630          | 0.2131   | 0.1912    | 0.2131 | 0.1632 | 0.4375 |
| No log        | 4.31  | 250  | 3.1590          | 0.2809   | 0.2107    | 0.2809 | 0.2096 | 0.4915 |
| No log        | 5.17  | 300  | 3.0569          | 0.3414   | 0.3012    | 0.3414 | 0.2825 | 0.5312 |
| No log        | 6.03  | 350  | 2.8798          | 0.3995   | 0.3279    | 0.3995 | 0.3298 | 0.5751 |
| No log        | 6.9   | 400  | 2.7761          | 0.4189   | 0.3461    | 0.4189 | 0.3522 | 0.5918 |
| No log        | 7.76  | 450  | 2.7086          | 0.4383   | 0.3693    | 0.4383 | 0.3689 | 0.6036 |
| 3.4503        | 8.62  | 500  | 2.6644          | 0.4576   | 0.4384    | 0.4576 | 0.3988 | 0.6165 |
| 3.4503        | 9.48  | 550  | 2.6426          | 0.4649   | 0.4400    | 0.4649 | 0.4021 | 0.6211 |


### Framework versions

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