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---
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-RUN4-25
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-RUN4-25
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: 1.7725
- Accuracy: 0.5731
- F1: 0.5731
- Precision: 0.5731
- Recall: 0.5731
## 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: 25
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.3427 | 1.0 | 472 | 1.2734 | 0.4056 | 0.4056 | 0.4056 | 0.4056 |
| 1.1941 | 2.0 | 944 | 1.1317 | 0.5129 | 0.5129 | 0.5129 | 0.5129 |
| 1.1178 | 3.0 | 1416 | 1.1461 | 0.5142 | 0.5142 | 0.5142 | 0.5142 |
| 1.0569 | 4.0 | 1888 | 1.0592 | 0.5412 | 0.5412 | 0.5412 | 0.5412 |
| 0.9925 | 5.0 | 2360 | 1.1219 | 0.5426 | 0.5426 | 0.5426 | 0.5426 |
| 0.9375 | 6.0 | 2832 | 1.0840 | 0.5740 | 0.5740 | 0.5740 | 0.5740 |
| 0.8771 | 7.0 | 3304 | 1.1091 | 0.5816 | 0.5816 | 0.5816 | 0.5816 |
| 0.8262 | 8.0 | 3776 | 1.1221 | 0.5851 | 0.5851 | 0.5851 | 0.5851 |
| 0.7871 | 9.0 | 4248 | 1.1499 | 0.5745 | 0.5745 | 0.5745 | 0.5745 |
| 0.7252 | 10.0 | 4720 | 1.3011 | 0.5621 | 0.5621 | 0.5621 | 0.5621 |
| 0.6919 | 11.0 | 5192 | 1.3272 | 0.5802 | 0.5802 | 0.5802 | 0.5802 |
| 0.6427 | 12.0 | 5664 | 1.3928 | 0.5683 | 0.5683 | 0.5683 | 0.5683 |
| 0.6008 | 13.0 | 6136 | 1.4789 | 0.5590 | 0.5590 | 0.5590 | 0.5590 |
| 0.5576 | 14.0 | 6608 | 1.4850 | 0.5638 | 0.5638 | 0.5638 | 0.5638 |
| 0.5267 | 15.0 | 7080 | 1.5124 | 0.5762 | 0.5762 | 0.5762 | 0.5762 |
| 0.4823 | 16.0 | 7552 | 1.3870 | 0.5683 | 0.5683 | 0.5683 | 0.5683 |
| 0.4564 | 17.0 | 8024 | 1.5277 | 0.5785 | 0.5785 | 0.5785 | 0.5785 |
| 0.4217 | 18.0 | 8496 | 1.5805 | 0.5723 | 0.5723 | 0.5723 | 0.5723 |
| 0.3891 | 19.0 | 8968 | 1.5173 | 0.5709 | 0.5709 | 0.5709 | 0.5709 |
| 0.3705 | 20.0 | 9440 | 1.6484 | 0.5807 | 0.5807 | 0.5807 | 0.5807 |
| 0.3419 | 21.0 | 9912 | 1.6999 | 0.5816 | 0.5816 | 0.5816 | 0.5816 |
| 0.321 | 22.0 | 10384 | 1.7024 | 0.5745 | 0.5745 | 0.5745 | 0.5745 |
| 0.3121 | 23.0 | 10856 | 1.7545 | 0.5709 | 0.5709 | 0.5709 | 0.5709 |
| 0.2964 | 24.0 | 11328 | 1.7355 | 0.5767 | 0.5767 | 0.5767 | 0.5767 |
| 0.285 | 25.0 | 11800 | 1.7725 | 0.5731 | 0.5731 | 0.5731 | 0.5731 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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