| --- |
| license: apache-2.0 |
| library_name: peft |
| tags: |
| - parquet |
| - text-classification |
| datasets: |
| - ag_news |
| metrics: |
| - accuracy |
| base_model: bert-large-uncased |
| model-index: |
| - name: bert-large-uncased-finetuned-lora-ag_news |
| results: |
| - task: |
| type: text-classification |
| name: Text Classification |
| dataset: |
| name: ag_news |
| type: ag_news |
| config: default |
| split: test |
| args: default |
| metrics: |
| - type: accuracy |
| value: 0.9332894736842106 |
| name: accuracy |
| --- |
| |
| <!-- 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. --> |
|
|
| # bert-large-uncased-finetuned-lora-ag_news |
| |
| This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the ag_news dataset. |
| It achieves the following results on the evaluation set: |
| - accuracy: 0.9333 |
|
|
| ## 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: 0.0004 |
| - train_batch_size: 24 |
| - eval_batch_size: 24 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 4 |
|
|
| ### Training results |
|
|
| | accuracy | train_loss | epoch | |
| |:--------:|:----------:|:-----:| |
| | 0.2497 | None | 0 | |
| | 0.9228 | 0.3117 | 0 | |
| | 0.9276 | 0.2198 | 1 | |
| | 0.9314 | 0.2014 | 2 | |
| | 0.9333 | 0.1888 | 3 | |
| |
| |
| ### Framework versions |
| |
| - PEFT 0.8.2 |
| - Transformers 4.37.2 |
| - Pytorch 2.2.0 |
| - Datasets 2.16.1 |
| - Tokenizers 0.15.2 |
