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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-filtered-115-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-filtered-115-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: 0.9056
- Accuracy: 0.6040
## 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: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 76 | 1.2568 | 0.4161 |
| No log | 2.0 | 152 | 1.1655 | 0.4603 |
| No log | 3.0 | 228 | 1.0574 | 0.5120 |
| No log | 4.0 | 304 | 0.9846 | 0.5574 |
| No log | 5.0 | 380 | 0.9665 | 0.5675 |
| No log | 6.0 | 456 | 0.9544 | 0.5738 |
| 1.0456 | 7.0 | 532 | 0.9503 | 0.5763 |
| 1.0456 | 8.0 | 608 | 0.9269 | 0.5876 |
| 1.0456 | 9.0 | 684 | 0.9233 | 0.5889 |
| 1.0456 | 10.0 | 760 | 0.9264 | 0.5927 |
| 1.0456 | 11.0 | 836 | 0.9092 | 0.5927 |
| 1.0456 | 12.0 | 912 | 0.9187 | 0.5914 |
| 1.0456 | 13.0 | 988 | 0.9122 | 0.6003 |
| 0.8486 | 14.0 | 1064 | 0.9091 | 0.5977 |
| 0.8486 | 15.0 | 1140 | 0.9079 | 0.5965 |
| 0.8486 | 16.0 | 1216 | 0.9144 | 0.5952 |
| 0.8486 | 17.0 | 1292 | 0.9049 | 0.5977 |
| 0.8486 | 18.0 | 1368 | 0.9257 | 0.5939 |
| 0.8486 | 19.0 | 1444 | 0.9006 | 0.5952 |
| 0.8112 | 20.0 | 1520 | 0.9008 | 0.6015 |
| 0.8112 | 21.0 | 1596 | 0.9044 | 0.6040 |
| 0.8112 | 22.0 | 1672 | 0.9008 | 0.6053 |
| 0.8112 | 23.0 | 1748 | 0.9052 | 0.6028 |
| 0.8112 | 24.0 | 1824 | 0.9065 | 0.6028 |
| 0.8112 | 25.0 | 1900 | 0.9015 | 0.6053 |
| 0.8112 | 26.0 | 1976 | 0.9141 | 0.5965 |
| 0.7992 | 27.0 | 2052 | 0.9072 | 0.6053 |
| 0.7992 | 28.0 | 2128 | 0.9042 | 0.6053 |
| 0.7992 | 29.0 | 2204 | 0.9054 | 0.6040 |
| 0.7992 | 30.0 | 2280 | 0.9056 | 0.6040 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2 |