| --- |
| library_name: peft |
| license: mit |
| base_model: roberta-base |
| tags: |
| - base_model:adapter:roberta-base |
| - lora |
| - transformers |
| metrics: |
| - accuracy |
| - matthews_correlation |
| - f1 |
| - precision |
| - recall |
| model-index: |
| - name: peft-roberta-base |
| 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. --> |
|
|
| # peft-roberta-base |
|
|
| This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0933 |
| - Accuracy: 0.9745 |
| - Matthews Correlation: 0.9662 |
| - F1: 0.9609 |
| - Precision: 0.9550 |
| - Recall: 0.9671 |
|
|
| ## 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: 0.0001 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 32 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 1 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Matthews Correlation | F1 | Precision | Recall | |
| |:-------------:|:------:|:----:|:---------------:|:--------:|:--------------------:|:------:|:---------:|:------:| |
| | 1.1892 | 0.1977 | 1400 | 0.2318 | 0.9216 | 0.8977 | 0.8968 | 0.8726 | 0.9270 | |
| | 0.6786 | 0.3954 | 2800 | 0.1395 | 0.9621 | 0.9497 | 0.9438 | 0.9332 | 0.9567 | |
| | 0.6029 | 0.5931 | 4200 | 0.1098 | 0.9696 | 0.9597 | 0.9558 | 0.9491 | 0.9629 | |
| | 0.5632 | 0.7908 | 5600 | 0.0951 | 0.9742 | 0.9658 | 0.9602 | 0.9539 | 0.9672 | |
| | 0.5216 | 0.9885 | 7000 | 0.0933 | 0.9745 | 0.9662 | 0.9609 | 0.9550 | 0.9671 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.18.1 |
| - Transformers 5.2.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
