--- license: apache-2.0 library_name: peft tags: - generated_from_trainer metrics: - accuracy base_model: albert/albert-base-v2 model-index: - name: NLI-Lora-Fine-Tuning-10K-ALBERTA results: [] --- # NLI-Lora-Fine-Tuning-10K-ALBERTA 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: 0.8439 - Accuracy: 0.6063 ## 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: 32 - eval_batch_size: 32 - 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 312 | 1.0562 | 0.4551 | | 1.0762 | 2.0 | 624 | 1.0236 | 0.4995 | | 1.0762 | 3.0 | 936 | 0.9603 | 0.5361 | | 1.0075 | 4.0 | 1248 | 0.9053 | 0.5671 | | 0.9178 | 5.0 | 1560 | 0.8796 | 0.5823 | | 0.9178 | 6.0 | 1872 | 0.8649 | 0.5934 | | 0.8859 | 7.0 | 2184 | 0.8551 | 0.5977 | | 0.8859 | 8.0 | 2496 | 0.8488 | 0.6033 | | 0.8632 | 9.0 | 2808 | 0.8450 | 0.6057 | | 0.8543 | 10.0 | 3120 | 0.8439 | 0.6063 | ### Framework versions - PEFT 0.9.0 - Transformers 4.38.2 - Pytorch 2.2.1+cu121 - Datasets 2.18.0 - Tokenizers 0.15.2