peft safetensors phi generated_from_trainer custom_code ar dataset:dalyaa/darebah6700 base_model:microsoft/phi-2 region:us
---
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