metadata
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: rv2307/electra-small-ner
model-index:
- name: >-
STS-Lora-Fine-Tuning-Capstone-electra-model-auto-cross-testing-123-final-pipes-value-error-solve
results: []
STS-Lora-Fine-Tuning-Capstone-electra-model-auto-cross-testing-123-final-pipes-value-error-solve
This model is a fine-tuned version of rv2307/electra-small-ner on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.7183
- Accuracy: 0.2727
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 180 | 1.7288 | 0.2429 |
| No log | 2.0 | 360 | 1.7230 | 0.2502 |
| 1.7009 | 3.0 | 540 | 1.7216 | 0.2676 |
| 1.7009 | 4.0 | 720 | 1.7216 | 0.2705 |
| 1.7009 | 5.0 | 900 | 1.7183 | 0.2748 |
| 1.6754 | 6.0 | 1080 | 1.7186 | 0.2748 |
| 1.6754 | 7.0 | 1260 | 1.7178 | 0.2741 |
| 1.6754 | 8.0 | 1440 | 1.7184 | 0.2748 |
| 1.6715 | 9.0 | 1620 | 1.7183 | 0.2741 |
| 1.6715 | 10.0 | 1800 | 1.7183 | 0.2727 |
Framework versions
- PEFT 0.10.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2