---
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_6
  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_6

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: 0.1212

## 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: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 7.3419        | 0.31  | 20   | 6.2616          |
| 4.0421        | 0.63  | 40   | 0.8963          |
| 0.6465        | 0.94  | 60   | 0.5726          |
| 0.4575        | 1.26  | 80   | 0.3999          |
| 0.309         | 1.57  | 100  | 0.3044          |
| 0.2531        | 1.89  | 120  | 0.2605          |
| 0.2235        | 2.2   | 140  | 0.2273          |
| 0.1922        | 2.52  | 160  | 0.2091          |
| 0.1793        | 2.83  | 180  | 0.1858          |
| 0.1488        | 3.14  | 200  | 0.1734          |
| 0.16          | 3.46  | 220  | 0.1646          |
| 0.1497        | 3.77  | 240  | 0.1557          |
| 0.1336        | 4.09  | 260  | 0.1489          |
| 0.1278        | 4.4   | 280  | 0.1415          |
| 0.1291        | 4.72  | 300  | 0.1392          |
| 0.1244        | 5.03  | 320  | 0.1342          |
| 0.1184        | 5.35  | 340  | 0.1319          |
| 0.118         | 5.66  | 360  | 0.1289          |
| 0.1153        | 5.97  | 380  | 0.1279          |
| 0.1052        | 6.29  | 400  | 0.1250          |
| 0.1058        | 6.6   | 420  | 0.1243          |
| 0.1142        | 6.92  | 440  | 0.1226          |
| 0.1026        | 7.23  | 460  | 0.1222          |
| 0.1051        | 7.55  | 480  | 0.1214          |
| 0.0977        | 7.86  | 500  | 0.1212          |


### Framework versions

- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.15.0