| library_name: peft | |
| license: apache-2.0 | |
| base_model: albert/albert-base-v2 | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - accuracy | |
| - f1 | |
| - precision | |
| - recall | |
| model-index: | |
| - name: results_lora | |
| 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. --> | |
| # results_lora | |
| This model is a fine-tuned version of [albert/albert-base-v2](https://huggingface.co/albert/albert-base-v2) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.2590 | |
| - Accuracy: 0.9014 | |
| - F1: 0.9044 | |
| - Precision: 0.8925 | |
| - Recall: 0.9167 | |
| ## 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: 3e-05 | |
| - train_batch_size: 16 | |
| - eval_batch_size: 64 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - lr_scheduler_warmup_steps: 500 | |
| - num_epochs: 3 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:| | |
| | 0.3298 | 1.0 | 4210 | 0.2669 | 0.8922 | 0.8934 | 0.8995 | 0.8874 | | |
| | 0.236 | 2.0 | 8420 | 0.2702 | 0.9048 | 0.9089 | 0.8865 | 0.9324 | | |
| | 0.1772 | 3.0 | 12630 | 0.2590 | 0.9014 | 0.9044 | 0.8925 | 0.9167 | | |
| ### Framework versions | |
| - PEFT 0.13.2 | |
| - Transformers 4.45.2 | |
| - Pytorch 2.5.0+cu124 | |
| - Datasets 3.0.1 | |
| - Tokenizers 0.20.1 |