---
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-42-with-lower-r-mid
  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-42-with-lower-r-mid

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: 1.4126
- Accuracy: 0.4199

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 90   | 1.7527          | 0.2429   |
| No log        | 2.0   | 180  | 1.7436          | 0.2429   |
| No log        | 3.0   | 270  | 1.7371          | 0.2429   |
| No log        | 4.0   | 360  | 1.7268          | 0.2444   |
| No log        | 5.0   | 450  | 1.7015          | 0.2973   |
| 1.6932        | 6.0   | 540  | 1.6853          | 0.2886   |
| 1.6932        | 7.0   | 630  | 1.6676          | 0.2922   |
| 1.6932        | 8.0   | 720  | 1.6423          | 0.3089   |
| 1.6932        | 9.0   | 810  | 1.6182          | 0.3191   |
| 1.6932        | 10.0  | 900  | 1.5953          | 0.3241   |
| 1.6932        | 11.0  | 990  | 1.5797          | 0.3256   |
| 1.5883        | 12.0  | 1080 | 1.5590          | 0.3358   |
| 1.5883        | 13.0  | 1170 | 1.5306          | 0.3539   |
| 1.5883        | 14.0  | 1260 | 1.5157          | 0.3561   |
| 1.5883        | 15.0  | 1350 | 1.4990          | 0.3604   |
| 1.5883        | 16.0  | 1440 | 1.4944          | 0.3611   |
| 1.4756        | 17.0  | 1530 | 1.4822          | 0.3698   |
| 1.4756        | 18.0  | 1620 | 1.4731          | 0.3735   |
| 1.4756        | 19.0  | 1710 | 1.4655          | 0.3756   |
| 1.4756        | 20.0  | 1800 | 1.4603          | 0.3778   |
| 1.4756        | 21.0  | 1890 | 1.4552          | 0.3974   |
| 1.4756        | 22.0  | 1980 | 1.4478          | 0.3930   |
| 1.4113        | 23.0  | 2070 | 1.4439          | 0.3901   |
| 1.4113        | 24.0  | 2160 | 1.4417          | 0.3930   |
| 1.4113        | 25.0  | 2250 | 1.4359          | 0.4075   |
| 1.4113        | 26.0  | 2340 | 1.4316          | 0.4126   |
| 1.4113        | 27.0  | 2430 | 1.4300          | 0.4061   |
| 1.3841        | 28.0  | 2520 | 1.4258          | 0.4141   |
| 1.3841        | 29.0  | 2610 | 1.4237          | 0.4162   |
| 1.3841        | 30.0  | 2700 | 1.4218          | 0.4133   |
| 1.3841        | 31.0  | 2790 | 1.4205          | 0.4213   |
| 1.3841        | 32.0  | 2880 | 1.4189          | 0.4133   |
| 1.3841        | 33.0  | 2970 | 1.4173          | 0.4162   |
| 1.3682        | 34.0  | 3060 | 1.4159          | 0.4220   |
| 1.3682        | 35.0  | 3150 | 1.4146          | 0.4199   |
| 1.3682        | 36.0  | 3240 | 1.4142          | 0.4213   |
| 1.3682        | 37.0  | 3330 | 1.4134          | 0.4213   |
| 1.3682        | 38.0  | 3420 | 1.4129          | 0.4199   |
| 1.3612        | 39.0  | 3510 | 1.4127          | 0.4184   |
| 1.3612        | 40.0  | 3600 | 1.4126          | 0.4199   |


### Framework versions

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