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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_4
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_4
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: 0.1176
## 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: 50
- training_steps: 500
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 8.1178 | 0.2 | 10 | 7.7550 |
| 7.3762 | 0.4 | 20 | 6.3827 |
| 4.9217 | 0.6 | 30 | 3.2172 |
| 1.7792 | 0.8 | 40 | 0.6700 |
| 0.5779 | 1.0 | 50 | 0.5969 |
| 0.4824 | 1.2 | 60 | 0.5149 |
| 0.4689 | 1.39 | 70 | 0.4440 |
| 0.3833 | 1.59 | 80 | 0.3862 |
| 0.2916 | 1.79 | 90 | 0.3364 |
| 0.2435 | 1.99 | 100 | 0.3013 |
| 0.2538 | 2.19 | 110 | 0.2779 |
| 0.2147 | 2.39 | 120 | 0.2619 |
| 0.1982 | 2.59 | 130 | 0.2453 |
| 0.2183 | 2.79 | 140 | 0.2275 |
| 0.1737 | 2.99 | 150 | 0.2148 |
| 0.1794 | 3.19 | 160 | 0.2068 |
| 0.1692 | 3.39 | 170 | 0.1949 |
| 0.1573 | 3.59 | 180 | 0.1864 |
| 0.1478 | 3.78 | 190 | 0.1788 |
| 0.164 | 3.98 | 200 | 0.1732 |
| 0.1454 | 4.18 | 210 | 0.1676 |
| 0.1279 | 4.38 | 220 | 0.1653 |
| 0.1544 | 4.58 | 230 | 0.1595 |
| 0.1206 | 4.78 | 240 | 0.1524 |
| 0.1334 | 4.98 | 250 | 0.1486 |
| 0.1342 | 5.18 | 260 | 0.1472 |
| 0.1061 | 5.38 | 270 | 0.1442 |
| 0.1265 | 5.58 | 280 | 0.1427 |
| 0.131 | 5.78 | 290 | 0.1389 |
| 0.1067 | 5.98 | 300 | 0.1374 |
| 0.1158 | 6.18 | 310 | 0.1331 |
| 0.1114 | 6.37 | 320 | 0.1323 |
| 0.1104 | 6.57 | 330 | 0.1311 |
| 0.108 | 6.77 | 340 | 0.1281 |
| 0.1015 | 6.97 | 350 | 0.1271 |
| 0.1 | 7.17 | 360 | 0.1262 |
| 0.1091 | 7.37 | 370 | 0.1242 |
| 0.1013 | 7.57 | 380 | 0.1230 |
| 0.1074 | 7.77 | 390 | 0.1233 |
| 0.0946 | 7.97 | 400 | 0.1226 |
| 0.0854 | 8.17 | 410 | 0.1222 |
| 0.0914 | 8.37 | 420 | 0.1205 |
| 0.1117 | 8.57 | 430 | 0.1198 |
| 0.0922 | 8.76 | 440 | 0.1194 |
| 0.1012 | 8.96 | 450 | 0.1185 |
| 0.0964 | 9.16 | 460 | 0.1185 |
| 0.0948 | 9.36 | 470 | 0.1181 |
| 0.0943 | 9.56 | 480 | 0.1178 |
| 0.0915 | 9.76 | 490 | 0.1176 |
| 0.0924 | 9.96 | 500 | 0.1176 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.15.0 |