--- license: apache-2.0 base_model: albert/albert-base-v2 tags: - generated_from_trainer metrics: - accuracy model-index: - name: kalai_bert_model_test_2 results: [] --- # kalai_bert_model_test_2 This model is a fine-tuned version of [albert/albert-base-v2](https://huggingface.co./albert/albert-base-v2) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.3276 - Accuracy: 0.93 ## 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 - num_epochs: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 25 | 0.5033 | 0.93 | | No log | 2.0 | 50 | 0.3276 | 0.93 | ### Framework versions - Transformers 4.40.0 - Pytorch 2.2.1+cu121 - Datasets 2.19.0 - Tokenizers 0.19.1