---
library_name: transformers
license: mit
base_model: intfloat/e5-small
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: intfloat-e5-small-arabic-fp16
  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. -->

# intfloat-e5-small-arabic-fp16

This model is a fine-tuned version of [intfloat/e5-small](https://huggingface.co/intfloat/e5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7833
- Accuracy: 0.6782
- Precision: 0.6650
- Recall: 0.6782
- F1: 0.6560

## 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     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.0984        | 0.3636 | 50   | 1.0847          | 0.4373   | 0.5309    | 0.4373 | 0.2662 |
| 1.069         | 0.7273 | 100  | 1.0270          | 0.5677   | 0.6816    | 0.5677 | 0.4864 |
| 1.0003        | 1.0873 | 150  | 0.9488          | 0.6041   | 0.6923    | 0.6041 | 0.5281 |
| 0.9438        | 1.4509 | 200  | 0.9085          | 0.6095   | 0.7017    | 0.6095 | 0.5340 |
| 0.9178        | 1.8145 | 250  | 0.9204          | 0.5895   | 0.6283    | 0.5895 | 0.5182 |
| 0.8936        | 2.1745 | 300  | 0.8394          | 0.6441   | 0.5970    | 0.6441 | 0.5653 |
| 0.8824        | 2.5382 | 350  | 0.8447          | 0.6464   | 0.7275    | 0.6464 | 0.5674 |
| 0.8774        | 2.9018 | 400  | 0.8706          | 0.625    | 0.6165    | 0.625  | 0.5859 |
| 0.8655        | 3.2618 | 450  | 0.8125          | 0.6541   | 0.6337    | 0.6541 | 0.6378 |
| 0.8517        | 3.6255 | 500  | 0.8528          | 0.6477   | 0.6565    | 0.6477 | 0.6013 |
| 0.8451        | 3.9891 | 550  | 0.7914          | 0.6686   | 0.6502    | 0.6686 | 0.6340 |
| 0.8084        | 4.3491 | 600  | 0.7833          | 0.6782   | 0.6650    | 0.6782 | 0.6560 |
| 0.8028        | 4.7127 | 650  | 0.7635          | 0.6923   | 0.6832    | 0.6923 | 0.6803 |
| 0.7874        | 5.0727 | 700  | 0.7815          | 0.6709   | 0.6828    | 0.6709 | 0.6754 |
| 0.7861        | 5.4364 | 750  | 0.7629          | 0.6873   | 0.6811    | 0.6873 | 0.6820 |
| 0.7593        | 5.8    | 800  | 0.7794          | 0.6823   | 0.6744    | 0.6823 | 0.6684 |
| 0.753         | 6.16   | 850  | 0.7680          | 0.6845   | 0.6859    | 0.6845 | 0.6838 |
| 0.753         | 6.5236 | 900  | 0.8404          | 0.6395   | 0.6783    | 0.6395 | 0.6459 |


### Framework versions

- Transformers 4.51.1
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1