metadata
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: bert-base-uncased
model-index:
- name: BERT-SA-LORA
results: []
BERT-SA-LORA
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3776
- Accuracy: 0.873
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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- 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 | 125 | 0.5379 | 0.74 |
| No log | 2.0 | 250 | 0.4962 | 0.78 |
| No log | 3.0 | 375 | 0.4127 | 0.827 |
| 0.4731 | 4.0 | 500 | 0.3871 | 0.849 |
| 0.4731 | 5.0 | 625 | 0.3720 | 0.861 |
| 0.4731 | 6.0 | 750 | 0.4096 | 0.858 |
| 0.4731 | 7.0 | 875 | 0.3971 | 0.869 |
| 0.2887 | 8.0 | 1000 | 0.3856 | 0.868 |
| 0.2887 | 9.0 | 1125 | 0.3751 | 0.872 |
| 0.2887 | 10.0 | 1250 | 0.3776 | 0.873 |
Framework versions
- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2