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---
license: mit
library_name: peft
tags:
- generated_from_trainer
base_model: microsoft/phi-2
model-index:
- name: phi2-QA-Arabic-phi-darebah-arabicandeng-newtest
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. -->
# phi2-QA-Arabic-phi-darebah-arabicandeng-newtest
This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6664
## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 1.3593 | 0.44 | 100 | 1.2815 |
| 1.1837 | 0.89 | 200 | 1.1457 |
| 1.0762 | 1.33 | 300 | 1.0660 |
| 0.9915 | 1.78 | 400 | 1.0016 |
| 0.9238 | 2.22 | 500 | 0.9568 |
| 0.9002 | 2.67 | 600 | 0.9155 |
| 0.8271 | 3.11 | 700 | 0.8798 |
| 0.8767 | 3.56 | 800 | 0.8471 |
| 0.8311 | 4.0 | 900 | 0.8225 |
| 0.7959 | 4.44 | 1000 | 0.8006 |
| 0.7031 | 4.89 | 1100 | 0.7836 |
| 0.761 | 5.33 | 1200 | 0.7618 |
| 0.7417 | 5.78 | 1300 | 0.7498 |
| 0.7258 | 6.22 | 1400 | 0.7319 |
| 0.6924 | 6.67 | 1500 | 0.7187 |
| 0.6622 | 7.11 | 1600 | 0.7127 |
| 0.6583 | 7.56 | 1700 | 0.6993 |
| 0.6851 | 8.0 | 1800 | 0.6924 |
| 0.6771 | 8.44 | 1900 | 0.6868 |
| 0.6832 | 8.89 | 2000 | 0.6805 |
| 0.6856 | 9.33 | 2100 | 0.6755 |
| 0.6747 | 9.78 | 2200 | 0.6724 |
| 0.659 | 10.22 | 2300 | 0.6691 |
| 0.657 | 10.67 | 2400 | 0.6674 |
| 0.6745 | 11.11 | 2500 | 0.6664 |
### Framework versions
- PEFT 0.7.2.dev0
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1 |