---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: emotions_6_classes_small
  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. -->

# emotions_6_classes_small

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the 'Audio emotions' public dataset, available form https://www.kaggle.com/datasets/uldisvalainis/audio-emotions.
'Surprised' class was discarded due to lack of samples.

It achieves the following results on the evaluation set:
- Loss: 0.9106
- Accuracy: 0.7920

## Model description

Classifies audios into 6 emotions:
- Angry
- Happy
- Sad
- Neutral
- Fearful
- Disgusted

## Intended uses & limitations

This model was trained for educational purposes.

## Training and evaluation data

- Training: 80%
- Test: 20%

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2009        | 0.99  | 19   | 0.6892          | 0.7891   |
| 0.2272        | 1.97  | 38   | 0.7235          | 0.7817   |
| 0.2196        | 2.96  | 57   | 0.7027          | 0.7809   |
| 0.2402        | 4.0   | 77   | 0.7953          | 0.7592   |
| 0.2301        | 4.99  | 96   | 0.7979          | 0.7699   |
| 0.1896        | 5.97  | 115  | 0.7533          | 0.7838   |
| 0.188         | 6.96  | 134  | 0.7483          | 0.7817   |
| 0.1573        | 8.0   | 154  | 0.8200          | 0.7756   |
| 0.1576        | 8.99  | 173  | 0.7623          | 0.7944   |
| 0.1452        | 9.97  | 192  | 0.7460          | 0.7944   |
| 0.1322        | 10.96 | 211  | 0.8031          | 0.7875   |
| 0.1353        | 12.0  | 231  | 0.7864          | 0.7883   |
| 0.1211        | 12.99 | 250  | 0.7934          | 0.7903   |
| 0.1165        | 13.97 | 269  | 0.7734          | 0.7936   |
| 0.0928        | 14.96 | 288  | 0.8743          | 0.7842   |
| 0.095         | 16.0  | 308  | 0.8483          | 0.7867   |
| 0.0824        | 16.99 | 327  | 0.8860          | 0.7850   |
| 0.0896        | 17.97 | 346  | 0.8314          | 0.7957   |
| 0.0874        | 18.96 | 365  | 0.8164          | 0.7936   |
| 0.081         | 20.0  | 385  | 0.8250          | 0.7993   |
| 0.0673        | 20.99 | 404  | 0.9118          | 0.7879   |
| 0.0716        | 21.97 | 423  | 0.8605          | 0.7912   |
| 0.0588        | 22.96 | 442  | 0.8470          | 0.7985   |
| 0.0579        | 24.0  | 462  | 0.8906          | 0.7920   |
| 0.0511        | 24.99 | 481  | 0.8853          | 0.7969   |
| 0.0488        | 25.97 | 500  | 0.8901          | 0.7973   |
| 0.0468        | 26.96 | 519  | 0.9083          | 0.7895   |
| 0.0505        | 28.0  | 539  | 0.9010          | 0.7903   |
| 0.0542        | 28.99 | 558  | 0.8924          | 0.7944   |
| 0.0542        | 29.61 | 570  | 0.9106          | 0.7920   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3