---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: wav2vec2-base-arabic_speech_emotion_recognition
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# wav2vec2-base-arabic_speech_emotion_recognition

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0430
- Accuracy: 0.9992
- Weighted f1: 0.9992
- Micro f1: 0.9992
- Macro f1: 0.9993
- Weighted recall: 0.9992
- Micro recall: 0.9992
- Macro recall: 0.9992
- Weighted precision: 0.9992
- Micro precision: 0.9992
- Macro precision: 0.9993

## 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 | Micro f1 | Macro f1 | Weighted recall | Micro recall | Macro recall | Weighted precision | Micro precision | Macro precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
| 1.6078        | 0.98  | 29   | 1.4403          | 0.5227   | 0.4478      | 0.5227   | 0.4426   | 0.5227          | 0.5227       | 0.5187       | 0.4200             | 0.5227          | 0.4145          |
| 1.6078        | 1.98  | 58   | 0.7310          | 0.9808   | 0.9808      | 0.9808   | 0.9809   | 0.9808          | 0.9808       | 0.9799       | 0.9816             | 0.9808          | 0.9827          |
| 1.6078        | 2.98  | 87   | 0.2797          | 0.9992   | 0.9992      | 0.9992   | 0.9993   | 0.9992          | 0.9992       | 0.9992       | 0.9992             | 0.9992          | 0.9993          |
| 1.6078        | 3.98  | 116  | 0.1361          | 0.9992   | 0.9992      | 0.9992   | 0.9993   | 0.9992          | 0.9992       | 0.9992       | 0.9992             | 0.9992          | 0.9993          |
| 1.6078        | 4.98  | 145  | 0.0855          | 0.9992   | 0.9992      | 0.9992   | 0.9993   | 0.9992          | 0.9992       | 0.9992       | 0.9992             | 0.9992          | 0.9993          |
| 1.6078        | 5.98  | 174  | 0.0638          | 0.9992   | 0.9992      | 0.9992   | 0.9993   | 0.9992          | 0.9992       | 0.9992       | 0.9992             | 0.9992          | 0.9993          |
| 1.6078        | 6.98  | 203  | 0.0529          | 0.9992   | 0.9992      | 0.9992   | 0.9993   | 0.9992          | 0.9992       | 0.9992       | 0.9992             | 0.9992          | 0.9993          |
| 1.6078        | 7.98  | 232  | 0.0470          | 0.9992   | 0.9992      | 0.9992   | 0.9993   | 0.9992          | 0.9992       | 0.9992       | 0.9992             | 0.9992          | 0.9993          |
| 1.6078        | 8.98  | 261  | 0.0440          | 0.9992   | 0.9992      | 0.9992   | 0.9993   | 0.9992          | 0.9992       | 0.9992       | 0.9992             | 0.9992          | 0.9993          |
| 1.6078        | 9.98  | 290  | 0.0430          | 0.9992   | 0.9992      | 0.9992   | 0.9993   | 0.9992          | 0.9992       | 0.9992       | 0.9992             | 0.9992          | 0.9993          |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.13.3