--- license: apache-2.0 library_name: peft tags: - generated_from_trainer base_model: google-bert/bert-base-uncased metrics: - accuracy - f1 model-index: - name: loha_fine_tuned_cb results: [] --- # loha_fine_tuned_cb This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co./google-bert/bert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 3.6524 - Accuracy: 0.3636 - F1: 0.2923 ## 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: 0.003 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - training_steps: 400 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-------:|:----:|:---------------:|:--------:|:------:| | 0.7795 | 3.5714 | 50 | 2.0073 | 0.3182 | 0.1536 | | 0.7479 | 7.1429 | 100 | 1.3794 | 0.3182 | 0.1536 | | 0.3979 | 10.7143 | 150 | 3.8538 | 0.3182 | 0.1536 | | 0.1064 | 14.2857 | 200 | 3.6640 | 0.3182 | 0.2636 | | 0.0423 | 17.8571 | 250 | 1.8668 | 0.4091 | 0.4067 | | 0.0025 | 21.4286 | 300 | 3.6246 | 0.4091 | 0.3208 | | 0.002 | 25.0 | 350 | 3.9578 | 0.4091 | 0.3208 | | 0.0023 | 28.5714 | 400 | 3.6524 | 0.3636 | 0.2923 | ### Framework versions - PEFT 0.10.1.dev0 - Transformers 4.40.1 - Pytorch 2.3.0 - Datasets 2.19.0 - Tokenizers 0.19.1