--- license: apache-2.0 base_model: PartAI/TookaBERT-Base tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: my_model results: [] --- # my_model This model is a fine-tuned version of [PartAI/TookaBERT-Base](https://huggingface.co./PartAI/TookaBERT-Base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.9495 - Precision: 0.5098 - Recall: 0.4866 - F1: 0.4979 - Accuracy: 0.8050 ## 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: 2 - eval_batch_size: 2 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | No log | 1.0 | 10 | 1.4199 | 0.3919 | 0.3102 | 0.3463 | 0.7206 | | No log | 2.0 | 20 | 1.2065 | 0.4497 | 0.3824 | 0.4133 | 0.7573 | | No log | 3.0 | 30 | 1.0512 | 0.4792 | 0.4305 | 0.4535 | 0.7759 | | No log | 4.0 | 40 | 0.9780 | 0.5056 | 0.4840 | 0.4945 | 0.8022 | | No log | 5.0 | 50 | 0.9495 | 0.5098 | 0.4866 | 0.4979 | 0.8050 | ### Framework versions - Transformers 4.42.4 - Pytorch 2.3.1+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1