---
license: mit
library_name: peft
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: microsoft/deberta-v3-xsmall
model-index:
- name: STS-Lora-Fine-Tuning-Capstone-Deberta-old-model-pipe-test_augmentation
  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. -->

# STS-Lora-Fine-Tuning-Capstone-Deberta-old-model-pipe-test_augmentation

This model is a fine-tuned version of [microsoft/deberta-v3-xsmall](https://huggingface.co/microsoft/deberta-v3-xsmall) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2431
- Accuracy: 0.4627

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 360  | 1.7500          | 0.2429   |
| 1.7474        | 2.0   | 720  | 1.7255          | 0.2451   |
| 1.681         | 3.0   | 1080 | 1.6291          | 0.3332   |
| 1.681         | 4.0   | 1440 | 1.4764          | 0.4130   |
| 1.5419        | 5.0   | 1800 | 1.4165          | 0.4159   |
| 1.4014        | 6.0   | 2160 | 1.3548          | 0.4336   |
| 1.3269        | 7.0   | 2520 | 1.3122          | 0.4456   |
| 1.3269        | 8.0   | 2880 | 1.3003          | 0.4529   |
| 1.2821        | 9.0   | 3240 | 1.2830          | 0.4572   |
| 1.2516        | 10.0  | 3600 | 1.2757          | 0.4576   |
| 1.2516        | 11.0  | 3960 | 1.2619          | 0.4590   |
| 1.2304        | 12.0  | 4320 | 1.2501          | 0.4670   |
| 1.2172        | 13.0  | 4680 | 1.2674          | 0.4583   |
| 1.2043        | 14.0  | 5040 | 1.2459          | 0.4656   |
| 1.2043        | 15.0  | 5400 | 1.2464          | 0.4627   |
| 1.1956        | 16.0  | 5760 | 1.2439          | 0.4645   |
| 1.1814        | 17.0  | 6120 | 1.2395          | 0.4648   |
| 1.1814        | 18.0  | 6480 | 1.2429          | 0.4637   |
| 1.1816        | 19.0  | 6840 | 1.2450          | 0.4634   |
| 1.1794        | 20.0  | 7200 | 1.2431          | 0.4627   |


### Framework versions

- PEFT 0.10.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2