---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: answerdotai-ModernBERT-base-arabic-fp16-allagree
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# answerdotai-ModernBERT-base-arabic-fp16-allagree

This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4267
- Accuracy: 0.8368
- Precision: 0.8342
- Recall: 0.8368
- F1: 0.8285

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.3
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.9706        | 0.7463 | 50   | 0.7251          | 0.7108   | 0.7096    | 0.7108 | 0.6814 |
| 1.3267        | 1.4925 | 100  | 0.5867          | 0.7677   | 0.7808    | 0.7677 | 0.7452 |
| 1.1549        | 2.2388 | 150  | 0.6251          | 0.7677   | 0.7919    | 0.7677 | 0.7325 |
| 1.0691        | 2.9851 | 200  | 0.4580          | 0.8330   | 0.8307    | 0.8330 | 0.8304 |
| 0.9217        | 3.7313 | 250  | 0.4803          | 0.8050   | 0.8245    | 0.8050 | 0.8115 |
| 0.7758        | 4.4776 | 300  | 0.4267          | 0.8368   | 0.8342    | 0.8368 | 0.8285 |
| 0.7288        | 5.2239 | 350  | 0.4726          | 0.8293   | 0.8280    | 0.8293 | 0.8201 |
| 0.5916        | 5.9701 | 400  | 0.4333          | 0.8368   | 0.8385    | 0.8368 | 0.8369 |
| 0.4328        | 6.7164 | 450  | 0.4511          | 0.8396   | 0.8374    | 0.8396 | 0.8383 |


### Framework versions

- Transformers 4.48.2
- Pytorch 2.6.0+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0