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---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: google-bert/bert-base-cased
model-index:
- name: STS-Lora-Fine-Tuning-Capstone-bert-testing-70-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-70-with-lower-r-mid
This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2732
- Accuracy: 0.4706
## 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 | 197 | 1.7537 | 0.2444 |
| No log | 2.0 | 394 | 1.7017 | 0.2886 |
| 1.6735 | 3.0 | 591 | 1.6479 | 0.2988 |
| 1.6735 | 4.0 | 788 | 1.5870 | 0.3169 |
| 1.6735 | 5.0 | 985 | 1.5191 | 0.3328 |
| 1.5268 | 6.0 | 1182 | 1.4680 | 0.3611 |
| 1.5268 | 7.0 | 1379 | 1.4300 | 0.3887 |
| 1.3747 | 8.0 | 1576 | 1.4043 | 0.4039 |
| 1.3747 | 9.0 | 1773 | 1.3854 | 0.4039 |
| 1.3747 | 10.0 | 1970 | 1.3713 | 0.4104 |
| 1.2814 | 11.0 | 2167 | 1.3599 | 0.4191 |
| 1.2814 | 12.0 | 2364 | 1.3560 | 0.4199 |
| 1.2408 | 13.0 | 2561 | 1.3407 | 0.4228 |
| 1.2408 | 14.0 | 2758 | 1.3234 | 0.4380 |
| 1.2408 | 15.0 | 2955 | 1.3233 | 0.4329 |
| 1.2136 | 16.0 | 3152 | 1.3146 | 0.4373 |
| 1.2136 | 17.0 | 3349 | 1.3181 | 0.4409 |
| 1.1914 | 18.0 | 3546 | 1.3267 | 0.4387 |
| 1.1914 | 19.0 | 3743 | 1.3103 | 0.4467 |
| 1.1914 | 20.0 | 3940 | 1.3056 | 0.4525 |
| 1.1759 | 21.0 | 4137 | 1.2887 | 0.4605 |
| 1.1759 | 22.0 | 4334 | 1.2917 | 0.4648 |
| 1.1661 | 23.0 | 4531 | 1.2955 | 0.4576 |
| 1.1661 | 24.0 | 4728 | 1.2841 | 0.4634 |
| 1.1661 | 25.0 | 4925 | 1.2850 | 0.4634 |
| 1.1566 | 26.0 | 5122 | 1.2998 | 0.4554 |
| 1.1566 | 27.0 | 5319 | 1.2854 | 0.4656 |
| 1.1482 | 28.0 | 5516 | 1.2792 | 0.4750 |
| 1.1482 | 29.0 | 5713 | 1.2809 | 0.4677 |
| 1.1482 | 30.0 | 5910 | 1.2777 | 0.4735 |
| 1.1407 | 31.0 | 6107 | 1.2799 | 0.4677 |
| 1.1407 | 32.0 | 6304 | 1.2816 | 0.4699 |
| 1.1417 | 33.0 | 6501 | 1.2802 | 0.4692 |
| 1.1417 | 34.0 | 6698 | 1.2739 | 0.4685 |
| 1.1417 | 35.0 | 6895 | 1.2739 | 0.4699 |
| 1.1391 | 36.0 | 7092 | 1.2745 | 0.4692 |
| 1.1391 | 37.0 | 7289 | 1.2733 | 0.4714 |
| 1.1391 | 38.0 | 7486 | 1.2729 | 0.4714 |
| 1.134 | 39.0 | 7683 | 1.2719 | 0.4706 |
| 1.134 | 40.0 | 7880 | 1.2732 | 0.4706 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2 |