--- library_name: peft license: apache-2.0 base_model: google-bert/bert-base-cased tags: - generated_from_trainer model-index: - name: gaudy-hound-390 results: [] --- # gaudy-hound-390 This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.4084 - Hamming Loss: 0.1123 - Zero One Loss: 1.0 - Jaccard Score: 1.0 - Hamming Loss Optimised: 0.1123 - Hamming Loss Threshold: 0.5944 - Zero One Loss Optimised: 1.0 - Zero One Loss Threshold: 0.9000 - Jaccard Score Optimised: 1.0 - Jaccard Score Threshold: 0.9000 ## 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: 8.858491651219974e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 2024 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Hamming Loss | Zero One Loss | Jaccard Score | Hamming Loss Optimised | Hamming Loss Threshold | Zero One Loss Optimised | Zero One Loss Threshold | Jaccard Score Optimised | Jaccard Score Threshold | |:-------------:|:-----:|:----:|:---------------:|:------------:|:-------------:|:-------------:|:----------------------:|:----------------------:|:-----------------------:|:-----------------------:|:-----------------------:|:-----------------------:| | No log | 1.0 | 100 | 0.5071 | 0.1129 | 1.0 | 1.0 | 0.1123 | 0.5944 | 1.0 | 0.9000 | 0.8716 | 0.3726 | | No log | 2.0 | 200 | 0.4179 | 0.1123 | 1.0 | 1.0 | 0.1123 | 0.5944 | 0.7662 | 0.3284 | 0.7638 | 0.3291 | | No log | 3.0 | 300 | 0.4084 | 0.1123 | 1.0 | 1.0 | 0.1123 | 0.5944 | 1.0 | 0.9000 | 1.0 | 0.9000 | ### Framework versions - PEFT 0.13.2 - Transformers 4.47.0 - Pytorch 2.5.1+cu124 - Datasets 3.1.0 - Tokenizers 0.21.0