--- license: mit base_model: cointegrated/rubert-tiny2 tags: - generated_from_trainer metrics: - accuracy model-index: - name: 128Bert results: [] --- # 128Bert This model is a fine-tuned version of [cointegrated/rubert-tiny2](https://huggingface.co/cointegrated/rubert-tiny2) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.8346 - Accuracy: 0.7033 ## 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: 1e-05 - train_batch_size: 128 - eval_batch_size: 128 - 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 | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 1.1934 | 1.0 | 2074 | 1.1488 | 0.6027 | | 1.0626 | 2.0 | 4148 | 1.0247 | 0.6459 | | 0.9729 | 3.0 | 6222 | 0.9483 | 0.6658 | | 0.908 | 4.0 | 8296 | 0.9041 | 0.6811 | | 0.8684 | 5.0 | 10370 | 0.8771 | 0.6897 | | 0.8348 | 6.0 | 12444 | 0.8593 | 0.6956 | | 0.8055 | 7.0 | 14518 | 0.8507 | 0.6991 | | 0.7924 | 8.0 | 16592 | 0.8410 | 0.7017 | | 0.7857 | 9.0 | 18666 | 0.8349 | 0.7037 | | 0.7732 | 10.0 | 20740 | 0.8346 | 0.7033 | ### Framework versions - Transformers 4.40.1 - Pytorch 2.2.1+cu121 - Datasets 2.19.0 - Tokenizers 0.19.1