--- license: apache-2.0 tags: - generated_from_trainer base_model: sentence-transformers/all-mpnet-base-v2 model-index: - name: action-policy-plans-classifier results: [] --- # action-policy-plans-classifier This model is a fine-tuned version of [sentence-transformers/all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6839 - Precision Micro: 0.7089 - Precision Weighted: 0.7043 - Precision Samples: 0.4047 - Recall Micro: 0.7066 - Recall Weighted: 0.7066 - Recall Samples: 0.4047 - F1-score: 0.4041 ## 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: 2.915e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 300 - num_epochs: 7 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision Micro | Precision Weighted | Precision Samples | Recall Micro | Recall Weighted | Recall Samples | F1-score | |:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------------:|:-----------------:|:------------:|:---------------:|:--------------:|:--------:| | 0.7333 | 1.0 | 253 | 0.5828 | 0.625 | 0.6422 | 0.4047 | 0.7098 | 0.7098 | 0.4065 | 0.4047 | | 0.5905 | 2.0 | 506 | 0.5593 | 0.6292 | 0.6318 | 0.4437 | 0.7760 | 0.7760 | 0.4446 | 0.4434 | | 0.4934 | 3.0 | 759 | 0.5269 | 0.6630 | 0.6637 | 0.4319 | 0.7571 | 0.7571 | 0.4347 | 0.4325 | | 0.4018 | 4.0 | 1012 | 0.5645 | 0.6449 | 0.6479 | 0.4456 | 0.7792 | 0.7792 | 0.4465 | 0.4453 | | 0.3235 | 5.0 | 1265 | 0.6101 | 0.6964 | 0.6929 | 0.4220 | 0.7382 | 0.7382 | 0.4229 | 0.4217 | | 0.2638 | 6.0 | 1518 | 0.6692 | 0.6888 | 0.6841 | 0.4111 | 0.7192 | 0.7192 | 0.4120 | 0.4108 | | 0.2197 | 7.0 | 1771 | 0.6839 | 0.7089 | 0.7043 | 0.4047 | 0.7066 | 0.7066 | 0.4047 | 0.4041 | ### Framework versions - Transformers 4.28.0 - Pytorch 2.0.1+cu118 - Datasets 2.12.0 - Tokenizers 0.13.3