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---
license: cc-by-4.0
library_name: peft
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: deepset/roberta-base-squad2
model-index:
- name: STS-Lora-Fine-Tuning-Capstone-roberta-base-deepset-test-111-with-higher-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-roberta-base-deepset-test-111-with-higher-r-mid
This model is a fine-tuned version of [deepset/roberta-base-squad2](https://huggingface.co/deepset/roberta-base-squad2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0593
- Accuracy: 0.5627
## 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: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 297 | 1.2901 | 0.4489 |
| 1.2919 | 2.0 | 594 | 1.1817 | 0.4931 |
| 1.2919 | 3.0 | 891 | 1.1639 | 0.4996 |
| 1.0546 | 4.0 | 1188 | 1.1222 | 0.5221 |
| 1.0546 | 5.0 | 1485 | 1.1199 | 0.5279 |
| 0.9971 | 6.0 | 1782 | 1.1256 | 0.5257 |
| 0.9606 | 7.0 | 2079 | 1.0944 | 0.5439 |
| 0.9606 | 8.0 | 2376 | 1.1414 | 0.5323 |
| 0.9423 | 9.0 | 2673 | 1.0932 | 0.5337 |
| 0.9423 | 10.0 | 2970 | 1.1029 | 0.5468 |
| 0.9171 | 11.0 | 3267 | 1.0914 | 0.5330 |
| 0.9069 | 12.0 | 3564 | 1.0582 | 0.5533 |
| 0.9069 | 13.0 | 3861 | 1.0677 | 0.5526 |
| 0.8954 | 14.0 | 4158 | 1.0817 | 0.5460 |
| 0.8954 | 15.0 | 4455 | 1.0703 | 0.5526 |
| 0.8926 | 16.0 | 4752 | 1.0724 | 0.5555 |
| 0.8845 | 17.0 | 5049 | 1.0583 | 0.5591 |
| 0.8845 | 18.0 | 5346 | 1.0749 | 0.5620 |
| 0.8666 | 19.0 | 5643 | 1.0559 | 0.5518 |
| 0.8666 | 20.0 | 5940 | 1.0660 | 0.5591 |
| 0.8602 | 21.0 | 6237 | 1.0620 | 0.5533 |
| 0.8582 | 22.0 | 6534 | 1.0891 | 0.5591 |
| 0.8582 | 23.0 | 6831 | 1.0565 | 0.5656 |
| 0.8539 | 24.0 | 7128 | 1.0680 | 0.5591 |
| 0.8539 | 25.0 | 7425 | 1.0556 | 0.5620 |
| 0.8551 | 26.0 | 7722 | 1.0605 | 0.5569 |
| 0.8512 | 27.0 | 8019 | 1.0560 | 0.5635 |
| 0.8512 | 28.0 | 8316 | 1.0552 | 0.5627 |
| 0.8505 | 29.0 | 8613 | 1.0599 | 0.5613 |
| 0.8505 | 30.0 | 8910 | 1.0593 | 0.5627 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2 |