metadata
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-21-with-lower-r
results: []
STS-Lora-Fine-Tuning-Capstone-bert-testing-21-with-lower-r
This model is a fine-tuned version of dslim/bert-base-NER on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.5146
- Accuracy: 0.3604
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 | 1.7493 | 0.2429 |
| No log | 2.0 | 360 | 1.7409 | 0.2444 |
| 1.7063 | 3.0 | 540 | 1.7315 | 0.2408 |
| 1.7063 | 4.0 | 720 | 1.7132 | 0.2741 |
| 1.7063 | 5.0 | 900 | 1.6786 | 0.2879 |
| 1.6653 | 6.0 | 1080 | 1.6617 | 0.2959 |
| 1.6653 | 7.0 | 1260 | 1.6399 | 0.3031 |
| 1.6653 | 8.0 | 1440 | 1.6109 | 0.3205 |
| 1.5949 | 9.0 | 1620 | 1.5937 | 0.3292 |
| 1.5949 | 10.0 | 1800 | 1.5715 | 0.3321 |
| 1.5949 | 11.0 | 1980 | 1.5627 | 0.3387 |
| 1.5344 | 12.0 | 2160 | 1.5543 | 0.3459 |
| 1.5344 | 13.0 | 2340 | 1.5396 | 0.3590 |
| 1.4932 | 14.0 | 2520 | 1.5295 | 0.3524 |
| 1.4932 | 15.0 | 2700 | 1.5270 | 0.3568 |
| 1.4932 | 16.0 | 2880 | 1.5240 | 0.3575 |
| 1.4738 | 17.0 | 3060 | 1.5177 | 0.3604 |
| 1.4738 | 18.0 | 3240 | 1.5185 | 0.3590 |
| 1.4738 | 19.0 | 3420 | 1.5156 | 0.3604 |
| 1.4609 | 20.0 | 3600 | 1.5146 | 0.3604 |
Framework versions
- PEFT 0.10.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2