peft safetensors generated_from_trainer base_model:microsoft/phi-2 license:other region:us
---
license: other
library_name: peft
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
base_model: microsoft/phi-2
model-index:
- name: Phi2-Seq-classification-LoRa
  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-Seq-classification-LoRa

This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5015
- Precision: 0.9783
- Recall: 0.8182
- F1-score: 0.8911
- Accuracy: 0.9236

## 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: 0.0002
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- training_steps: 3000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1-score | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:--------:|
| 0.3914        | 0.7   | 100  | 0.5650          | 0.8571    | 0.6545 | 0.7423   | 0.8264   |
| 0.0065        | 1.39  | 200  | 0.8945          | 0.9375    | 0.8182 | 0.8738   | 0.9097   |
| 0.2111        | 2.09  | 300  | 0.6418          | 0.9388    | 0.8364 | 0.8846   | 0.9167   |
| 0.1823        | 2.78  | 400  | 0.5655          | 0.9773    | 0.7818 | 0.8687   | 0.9097   |
| 0.145         | 3.48  | 500  | 0.9232          | 0.9545    | 0.7636 | 0.8485   | 0.8958   |
| 0.1095        | 4.17  | 600  | 0.8011          | 0.9583    | 0.8364 | 0.8932   | 0.9236   |
| 0.0           | 4.87  | 700  | 0.9774          | 0.9796    | 0.8727 | 0.9231   | 0.9444   |
| 0.4204        | 5.57  | 800  | 0.6787          | 0.96      | 0.8727 | 0.9143   | 0.9375   |
| 0.0068        | 6.26  | 900  | 1.1916          | 0.9783    | 0.8182 | 0.8911   | 0.9236   |
| 0.0004        | 6.96  | 1000 | 0.9468          | 0.9783    | 0.8182 | 0.8911   | 0.9236   |
| 0.0           | 7.65  | 1100 | 1.2818          | 0.9787    | 0.8364 | 0.9020   | 0.9306   |
| 0.0           | 8.35  | 1200 | 1.2332          | 0.9787    | 0.8364 | 0.9020   | 0.9306   |
| 0.0           | 9.04  | 1300 | 1.3078          | 0.9583    | 0.8364 | 0.8932   | 0.9236   |
| 0.0           | 9.74  | 1400 | 1.9713          | 0.9773    | 0.7818 | 0.8687   | 0.9097   |
| 0.0001        | 10.43 | 1500 | 1.5254          | 0.9773    | 0.7818 | 0.8687   | 0.9097   |
| 0.0           | 11.13 | 1600 | 1.8045          | 0.9592    | 0.8545 | 0.9038   | 0.9306   |
| 0.0011        | 11.83 | 1700 | 2.7594          | 0.9574    | 0.8182 | 0.8824   | 0.9167   |
| 0.0           | 12.52 | 1800 | 1.9378          | 0.9592    | 0.8545 | 0.9038   | 0.9306   |
| 0.0           | 13.22 | 1900 | 1.8710          | 0.9592    | 0.8545 | 0.9038   | 0.9306   |
| 0.0           | 13.91 | 2000 | 1.8685          | 0.9592    | 0.8545 | 0.9038   | 0.9306   |
| 0.0           | 14.61 | 2100 | 1.8683          | 0.9592    | 0.8545 | 0.9038   | 0.9306   |
| 0.0384        | 15.3  | 2200 | 2.3028          | 0.9592    | 0.8545 | 0.9038   | 0.9306   |
| 0.001         | 16.0  | 2300 | 1.7787          | 0.9216    | 0.8545 | 0.8868   | 0.9167   |
| 0.0           | 16.7  | 2400 | 1.8615          | 0.9787    | 0.8364 | 0.9020   | 0.9306   |
| 0.8746        | 17.39 | 2500 | 2.6710          | 0.9756    | 0.7273 | 0.8333   | 0.8889   |
| 0.0           | 18.09 | 2600 | 1.0475          | 0.9412    | 0.8727 | 0.9057   | 0.9306   |
| 0.0           | 18.78 | 2700 | 2.3325          | 0.9778    | 0.8    | 0.8800   | 0.9167   |
| 0.0001        | 19.48 | 2800 | 1.3658          | 0.94      | 0.8545 | 0.8952   | 0.9236   |
| 0.0           | 20.17 | 2900 | 2.4668          | 0.9783    | 0.8182 | 0.8911   | 0.9236   |
| 0.0           | 20.87 | 3000 | 2.5015          | 0.9783    | 0.8182 | 0.8911   | 0.9236   |


### Framework versions

- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0