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---
language:
- ar
library_name: peft
tags:
- generated_from_trainer
datasets:
- dalyaa/darebah2400
base_model: microsoft/phi-2
model-index:
- name: phi-2
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. -->
# phi-2
This model is a fine-tuned version of [microsoftl](https://huggingface.co/microsoftl) on the dalyaa/darebah2400 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8345
## 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: 2.5e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- training_steps: 2500
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.1815 | 0.4 | 100 | 1.1010 |
| 0.984 | 0.8 | 200 | 0.9893 |
| 0.8706 | 1.2 | 300 | 0.9545 |
| 0.8095 | 1.6 | 400 | 0.9203 |
| 0.767 | 2.0 | 500 | 0.9030 |
| 0.7439 | 2.4 | 600 | 0.8878 |
| 0.7163 | 2.8 | 700 | 0.8716 |
| 0.671 | 3.2 | 800 | 0.8679 |
| 0.679 | 3.6 | 900 | 0.8587 |
| 0.6585 | 4.0 | 1000 | 0.8586 |
| 0.6528 | 4.4 | 1100 | 0.8535 |
| 0.6238 | 4.8 | 1200 | 0.8501 |
| 0.6041 | 5.2 | 1300 | 0.8434 |
| 0.6011 | 5.6 | 1400 | 0.8471 |
| 0.6386 | 6.0 | 1500 | 0.8379 |
| 0.6288 | 6.4 | 1600 | 0.8374 |
| 0.5823 | 6.8 | 1700 | 0.8409 |
| 0.6074 | 7.2 | 1800 | 0.8363 |
| 0.5944 | 7.6 | 1900 | 0.8367 |
| 0.5918 | 8.0 | 2000 | 0.8412 |
| 0.5931 | 8.4 | 2100 | 0.8343 |
| 0.5624 | 8.8 | 2200 | 0.8363 |
| 0.5709 | 9.2 | 2300 | 0.8354 |
| 0.5783 | 9.6 | 2400 | 0.8354 |
| 0.5933 | 10.0 | 2500 | 0.8345 |
### Framework versions
- PEFT 0.8.2
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1 |