| | --- |
| | license: apache-2.0 |
| | base_model: bert-base-uncased |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - imdb |
| | metrics: |
| | - accuracy |
| | - f1 |
| | model-index: |
| | - name: bert-base-uncased-lora-text-classification |
| | results: [] |
| | --- |
| | |
| | <!-- 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-base-uncased-lora-text-classification |
| |
|
| | This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the imdb dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2267 |
| | - Accuracy: {'accuracy': 0.92824} |
| | - F1: 0.9288 |
| |
|
| | ## 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: 0.001 |
| | - train_batch_size: 16 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 5 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| | |:-------------:|:-----:|:----:|:---------------:|:---------------------:|:------:| |
| | | 0.2608 | 1.0 | 1563 | 0.2187 | {'accuracy': 0.91768} | 0.9177 | |
| | | 0.246 | 2.0 | 3126 | 0.2070 | {'accuracy': 0.92096} | 0.9205 | |
| | | 0.2056 | 3.0 | 4689 | 0.2051 | {'accuracy': 0.92572} | 0.9259 | |
| | | 0.1748 | 4.0 | 6252 | 0.2570 | {'accuracy': 0.92288} | 0.9249 | |
| | | 0.1494 | 5.0 | 7815 | 0.2267 | {'accuracy': 0.92824} | 0.9288 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.35.2 |
| | - Pytorch 2.1.0+cu118 |
| | - Datasets 2.15.0 |
| | - Tokenizers 0.15.0 |
| |
|
