metadata
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: bert-base-uncased
datasets:
- swag
metrics:
- accuracy
model-index:
- name: fine-tuned-bert-base-uncased-swag-peft
results: []
fine-tuned-bert-base-uncased-swag-peft
This model is a fine-tuned version of bert-base-uncased on the swag dataset. It achieves the following results on the evaluation set:
- Loss: 0.6557
- Accuracy: 0.7483
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: 1.5e-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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.0316 | 1.0 | 1150 | 0.8202 | 0.6860 |
| 0.9261 | 2.0 | 2300 | 0.7423 | 0.7144 |
| 0.8862 | 3.0 | 3450 | 0.7114 | 0.7268 |
| 0.8612 | 4.0 | 4600 | 0.6924 | 0.7347 |
| 0.8637 | 5.0 | 5750 | 0.6819 | 0.7393 |
| 0.8541 | 6.0 | 6900 | 0.6691 | 0.7441 |
| 0.8369 | 7.0 | 8050 | 0.6635 | 0.7464 |
| 0.8349 | 8.0 | 9200 | 0.6591 | 0.7475 |
| 0.8302 | 9.0 | 10350 | 0.6572 | 0.7483 |
| 0.8333 | 10.0 | 11500 | 0.6557 | 0.7483 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1