---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
base_model: CAMeL-Lab/bert-base-arabic-camelbert-ca
model-index:
- name: POEMS-CAMELBERT-CA-RUN4
  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. -->

# POEMS-CAMELBERT-CA-RUN4

This model is a fine-tuned version of [CAMeL-Lab/bert-base-arabic-camelbert-ca](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-ca) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1498
- Accuracy: 0.5966
- F1: 0.5966
- Precision: 0.5966
- Recall: 0.5966

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.3444        | 1.0   | 472  | 1.2277          | 0.4552   | 0.4552 | 0.4552    | 0.4552 |
| 1.1589        | 2.0   | 944  | 1.0866          | 0.5275   | 0.5275 | 0.5275    | 0.5275 |
| 1.0829        | 3.0   | 1416 | 1.1405          | 0.5146   | 0.5146 | 0.5146    | 0.5146 |
| 1.0           | 4.0   | 1888 | 1.0262          | 0.5643   | 0.5643 | 0.5643    | 0.5643 |
| 0.9288        | 5.0   | 2360 | 1.0574          | 0.5762   | 0.5762 | 0.5762    | 0.5762 |
| 0.8776        | 6.0   | 2832 | 1.0456          | 0.5838   | 0.5838 | 0.5838    | 0.5838 |
| 0.8166        | 7.0   | 3304 | 1.1421          | 0.5745   | 0.5745 | 0.5745    | 0.5745 |
| 0.7636        | 8.0   | 3776 | 1.0959          | 0.5931   | 0.5931 | 0.5931    | 0.5931 |
| 0.7173        | 9.0   | 4248 | 1.1400          | 0.5851   | 0.5851 | 0.5851    | 0.5851 |
| 0.6915        | 10.0  | 4720 | 1.1498          | 0.5966   | 0.5966 | 0.5966    | 0.5966 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2