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---
license: mit
library_name: peft
tags:
- generated_from_trainer
base_model: microsoft/phi-2
model-index:
- name: fine-tuning-Phi2-with-webglm-qa-with-lora_8
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. -->
# fine-tuning-Phi2-with-webglm-qa-with-lora_8
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: 0.0935
## 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 5
- total_train_batch_size: 10
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 60
- training_steps: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 7.1823 | 0.31 | 20 | 6.1082 |
| 4.0 | 0.63 | 40 | 0.9863 |
| 0.7159 | 0.94 | 60 | 0.6293 |
| 0.4994 | 1.26 | 80 | 0.4239 |
| 0.3187 | 1.57 | 100 | 0.3044 |
| 0.251 | 1.89 | 120 | 0.2567 |
| 0.2189 | 2.2 | 140 | 0.2206 |
| 0.1869 | 2.52 | 160 | 0.2000 |
| 0.1741 | 2.83 | 180 | 0.1781 |
| 0.1439 | 3.14 | 200 | 0.1638 |
| 0.1543 | 3.46 | 220 | 0.1550 |
| 0.1428 | 3.77 | 240 | 0.1455 |
| 0.127 | 4.09 | 260 | 0.1394 |
| 0.1206 | 4.4 | 280 | 0.1314 |
| 0.1206 | 4.72 | 300 | 0.1298 |
| 0.1162 | 5.03 | 320 | 0.1246 |
| 0.109 | 5.35 | 340 | 0.1235 |
| 0.1088 | 5.66 | 360 | 0.1190 |
| 0.1062 | 5.97 | 380 | 0.1157 |
| 0.0938 | 6.29 | 400 | 0.1146 |
| 0.0945 | 6.6 | 420 | 0.1133 |
| 0.1012 | 6.92 | 440 | 0.1105 |
| 0.0881 | 7.23 | 460 | 0.1109 |
| 0.0897 | 7.55 | 480 | 0.1091 |
| 0.0837 | 7.86 | 500 | 0.1060 |
| 0.0899 | 8.18 | 520 | 0.1051 |
| 0.0803 | 8.49 | 540 | 0.1041 |
| 0.0792 | 8.81 | 560 | 0.1021 |
| 0.0885 | 9.12 | 580 | 0.1000 |
| 0.0844 | 9.43 | 600 | 0.1004 |
| 0.0704 | 9.75 | 620 | 0.0992 |
| 0.0681 | 10.06 | 640 | 0.0994 |
| 0.0727 | 10.38 | 660 | 0.0977 |
| 0.0712 | 10.69 | 680 | 0.0970 |
| 0.073 | 11.01 | 700 | 0.0971 |
| 0.0683 | 11.32 | 720 | 0.0974 |
| 0.0682 | 11.64 | 740 | 0.0964 |
| 0.0716 | 11.95 | 760 | 0.0962 |
| 0.0645 | 12.26 | 780 | 0.0948 |
| 0.0662 | 12.58 | 800 | 0.0947 |
| 0.0677 | 12.89 | 820 | 0.0947 |
| 0.0626 | 13.21 | 840 | 0.0953 |
| 0.0628 | 13.52 | 860 | 0.0946 |
| 0.0642 | 13.84 | 880 | 0.0937 |
| 0.0641 | 14.15 | 900 | 0.0939 |
| 0.0587 | 14.47 | 920 | 0.0939 |
| 0.0664 | 14.78 | 940 | 0.0933 |
| 0.061 | 15.09 | 960 | 0.0931 |
| 0.0596 | 15.41 | 980 | 0.0934 |
| 0.0646 | 15.72 | 1000 | 0.0935 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.15.0 |