---
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: 3.4231
- Accuracy: 0.0993
- Precision: 0.0191
- Recall: 0.0993
- F1: 0.0296
- Binary: 0.3603

## 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   | 4.4031          | 0.0218   | 0.0042    | 0.0218 | 0.0061 | 0.1886 |
| No log        | 1.72  | 100  | 4.1752          | 0.0363   | 0.0204    | 0.0363 | 0.0100 | 0.3102 |
| No log        | 2.59  | 150  | 3.9334          | 0.0363   | 0.0159    | 0.0363 | 0.0125 | 0.3102 |
| No log        | 3.45  | 200  | 3.7751          | 0.0557   | 0.0270    | 0.0557 | 0.0268 | 0.3266 |
| No log        | 4.31  | 250  | 3.6877          | 0.0775   | 0.0241    | 0.0775 | 0.0314 | 0.3383 |
| No log        | 5.17  | 300  | 3.5839          | 0.0920   | 0.0220    | 0.0920 | 0.0329 | 0.3550 |
| No log        | 6.03  | 350  | 3.5119          | 0.0920   | 0.0219    | 0.0920 | 0.0327 | 0.3586 |
| No log        | 6.9   | 400  | 3.4851          | 0.0872   | 0.0274    | 0.0872 | 0.0283 | 0.3508 |
| No log        | 7.76  | 450  | 3.4593          | 0.0920   | 0.0221    | 0.0920 | 0.0312 | 0.3552 |
| 3.8751        | 8.62  | 500  | 3.4240          | 0.1017   | 0.0223    | 0.1017 | 0.0328 | 0.3610 |
| 3.8751        | 9.48  | 550  | 3.4231          | 0.0993   | 0.0191    | 0.0993 | 0.0296 | 0.3603 |


### Framework versions

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