---
license: apache-2.0
base_model: othrif/wav2vec2-large-xlsr-arabic
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- f1
model-index:
- name: sentiment_analysis_model
  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. -->

# sentiment_analysis_model

This model is a fine-tuned version of [othrif/wav2vec2-large-xlsr-arabic](https://huggingface.co/othrif/wav2vec2-large-xlsr-arabic) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3312
- Accuracy: 0.7107
- Precision: 0.1777
- F1: 0.2077

## 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: 1e-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: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|
| No log        | 1.0   | 4    | 1.3312          | 0.7107   | 0.1777    | 0.2077 |
| No log        | 2.0   | 8    | 1.2993          | 0.7107   | 0.1777    | 0.2077 |
| 1.3368        | 3.0   | 12   | 1.2879          | 0.7107   | 0.1777    | 0.2077 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu118
- Datasets 2.14.5
- Tokenizers 0.15.2