---
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- generated_from_trainer
datasets:
- shemo
metrics:
- f1
model-index:
- name: results
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: shemo
      type: shemo
      config: clean
      split: None
      args: clean
    metrics:
    - name: F1
      type: f1
      value: 0.8335174497965196
---

<!-- 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. -->

# results

This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the shemo dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6161
- F1: 0.8335

## Labels description

- 0 : anger
- 1 : happiness
- 2 : neutral
- 3 : sadness

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 25
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.1127        | 1.0   | 154  | 0.9244          | 0.3968 |
| 0.6982        | 2.0   | 308  | 0.5642          | 0.6435 |
| 0.6246        | 3.0   | 462  | 0.5049          | 0.6273 |
| 0.5097        | 4.0   | 616  | 0.4282          | 0.7246 |
| 0.4496        | 5.0   | 770  | 0.3280          | 0.8158 |
| 0.4476        | 6.0   | 924  | 0.4663          | 0.7978 |
| 0.2212        | 7.0   | 1078 | 0.3253          | 0.8641 |
| 0.1548        | 8.0   | 1232 | 0.9445          | 0.7420 |
| 0.3829        | 9.0   | 1386 | 0.7194          | 0.7880 |
| 0.0773        | 10.0  | 1540 | 0.5301          | 0.8657 |
| 0.2481        | 11.0  | 1694 | 0.5321          | 0.8812 |
| 0.0597        | 12.0  | 1848 | 0.6161          | 0.8335 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1