--- license: apache-2.0 base_model: albert-base-v2 tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: Albert-finetuned-stationary-update results: [] --- # Albert-finetuned-stationary-update This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.7542 - Accuracy: 0.5967 - F1: 0.5862 ## 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: 2e-05 - train_batch_size: 64 - eval_batch_size: 64 - 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 | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | 0.3976 | 1.0 | 38 | 0.8830 | 0.6033 | 0.5849 | | 0.3105 | 2.0 | 76 | 0.9030 | 0.63 | 0.5876 | | 0.2256 | 3.0 | 114 | 1.2156 | 0.6333 | 0.6366 | | 0.1788 | 4.0 | 152 | 1.3055 | 0.6 | 0.5857 | | 0.161 | 5.0 | 190 | 1.2205 | 0.59 | 0.5808 | | 0.1304 | 6.0 | 228 | 1.5496 | 0.5933 | 0.5804 | | 0.1046 | 7.0 | 266 | 1.6266 | 0.59 | 0.5915 | | 0.0966 | 8.0 | 304 | 1.6807 | 0.6033 | 0.5971 | | 0.0649 | 9.0 | 342 | 1.7279 | 0.5967 | 0.5831 | | 0.0697 | 10.0 | 380 | 1.7542 | 0.5967 | 0.5862 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu118 - Datasets 2.15.0 - Tokenizers 0.15.0