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---
language:
- ar
library_name: peft
tags:
- generated_from_trainer
datasets:
- dalyaa/darebah6700
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/darebah6700 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8023
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.2748 | 0.15 | 100 | 1.1349 |
| 1.1095 | 0.29 | 200 | 1.0077 |
| 1.0138 | 0.44 | 300 | 0.9587 |
| 0.9506 | 0.58 | 400 | 0.9188 |
| 0.9047 | 0.73 | 500 | 0.8906 |
| 0.9017 | 0.87 | 600 | 0.8722 |
| 0.8872 | 1.02 | 700 | 0.8660 |
| 0.8744 | 1.16 | 800 | 0.8501 |
| 0.8221 | 1.31 | 900 | 0.8472 |
| 0.8356 | 1.45 | 1000 | 0.8380 |
| 0.8335 | 1.6 | 1100 | 0.8317 |
| 0.828 | 1.75 | 1200 | 0.8273 |
| 0.8307 | 1.89 | 1300 | 0.8231 |
| 0.8147 | 2.04 | 1400 | 0.8185 |
| 0.8012 | 2.18 | 1500 | 0.8139 |
| 0.7885 | 2.33 | 1600 | 0.8129 |
| 0.7831 | 2.47 | 1700 | 0.8102 |
| 0.7787 | 2.62 | 1800 | 0.8148 |
| 0.7921 | 2.76 | 1900 | 0.8083 |
| 0.7777 | 2.91 | 2000 | 0.8073 |
| 0.7766 | 3.05 | 2100 | 0.8045 |
| 0.7658 | 3.2 | 2200 | 0.8056 |
| 0.7651 | 3.35 | 2300 | 0.8044 |
| 0.7844 | 3.49 | 2400 | 0.8023 |
| 0.7876 | 3.64 | 2500 | 0.8023 |
### Framework versions
- PEFT 0.8.2
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1 |