---
license: mit
library_name: peft
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: dslim/bert-base-NER
model-index:
- name: STS-Lora-Fine-Tuning-Capstone-bert-testing-22-with-lower-r
  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-bert-testing-22-with-lower-r

This model is a fine-tuned version of [dslim/bert-base-NER](https://huggingface.co/dslim/bert-base-NER) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4650
- Accuracy: 0.3843

## 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   | 180  | 1.7491          | 0.2429   |
| No log        | 2.0   | 360  | 1.7398          | 0.2451   |
| 1.7057        | 3.0   | 540  | 1.7266          | 0.2408   |
| 1.7057        | 4.0   | 720  | 1.6996          | 0.2922   |
| 1.7057        | 5.0   | 900  | 1.6538          | 0.2988   |
| 1.6492        | 6.0   | 1080 | 1.6283          | 0.3118   |
| 1.6492        | 7.0   | 1260 | 1.5879          | 0.3270   |
| 1.6492        | 8.0   | 1440 | 1.5578          | 0.3387   |
| 1.5479        | 9.0   | 1620 | 1.5355          | 0.3503   |
| 1.5479        | 10.0  | 1800 | 1.5148          | 0.3561   |
| 1.5479        | 11.0  | 1980 | 1.5062          | 0.3561   |
| 1.4735        | 12.0  | 2160 | 1.5005          | 0.3691   |
| 1.4735        | 13.0  | 2340 | 1.4876          | 0.3843   |
| 1.437         | 14.0  | 2520 | 1.4799          | 0.3800   |
| 1.437         | 15.0  | 2700 | 1.4768          | 0.3785   |
| 1.437         | 16.0  | 2880 | 1.4732          | 0.3851   |
| 1.4223        | 17.0  | 3060 | 1.4689          | 0.3800   |
| 1.4223        | 18.0  | 3240 | 1.4684          | 0.3822   |
| 1.4223        | 19.0  | 3420 | 1.4657          | 0.3822   |
| 1.4123        | 20.0  | 3600 | 1.4650          | 0.3843   |


### Framework versions

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