--- license: apache-2.0 base_model: albert-base-v2 tags: - generated_from_trainer model-index: - name: output results: [] --- # output 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: 0.0000 - Overall Precision: 1.0 - Overall Recall: 1.0 - Overall F1: 1.0 - Overall Accuracy: 1.0 - D622 F1: 1.0 - O Isin F1: 1.0 ## 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: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 10 - num_epochs: 1 ### Training results | Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | D622 F1 | O Isin F1 | |:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:-------:|:---------:| | 0.0 | 1.0 | 461 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | ### Framework versions - Transformers 4.43.3 - Pytorch 2.4.0 - Datasets 2.20.0 - Tokenizers 0.19.1