---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: audio_emotion_classification
  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. -->

# audio_emotion_classification

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0104
- Accuracy: 1.0
- Precision: 1.0
- Recall: 1.0
- F1: 1.0

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1  |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:---:|
| No log        | 1.0   | 240  | 0.1119          | 1.0      | 1.0       | 1.0    | 1.0 |
| No log        | 2.0   | 480  | 0.0285          | 1.0      | 1.0       | 1.0    | 1.0 |
| 0.4242        | 3.0   | 720  | 0.0159          | 1.0      | 1.0       | 1.0    | 1.0 |
| 0.4242        | 4.0   | 960  | 0.0116          | 1.0      | 1.0       | 1.0    | 1.0 |
| 0.0253        | 5.0   | 1200 | 0.0104          | 1.0      | 1.0       | 1.0    | 1.0 |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Tokenizers 0.20.3