--- license: apache-2.0 base_model: docketanalyzer/docket-lm-xs tags: - generated_from_trainer metrics: - f1 model-index: - name: label-complaint results: [] --- # label-complaint This model is a fine-tuned version of [docketanalyzer/docket-lm-xs](https://huggingface.co/docketanalyzer/docket-lm-xs) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0015 - F1: 0.9995 ## 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: 5e-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 - lr_scheduler_warmup_ratio: 0.02 - num_epochs: 1 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | |:-------------:|:-----:|:----:|:---------------:|:------:| | 0.0013 | 0.08 | 380 | 0.0054 | 0.9983 | | 0.0007 | 0.16 | 760 | 0.0139 | 0.9976 | | 0.0003 | 0.24 | 1140 | 0.0061 | 0.9985 | | 0.0002 | 0.32 | 1520 | 0.0109 | 0.9981 | | 0.0005 | 0.4 | 1900 | 0.0093 | 0.9985 | | 0.0002 | 0.48 | 2280 | 0.0080 | 0.9988 | | 0.0004 | 0.56 | 2660 | 0.0099 | 0.9978 | | 0.0004 | 0.64 | 3040 | 0.0024 | 0.9990 | | 0.0002 | 0.72 | 3420 | 0.0037 | 0.9988 | | 0.0003 | 0.8 | 3800 | 0.0013 | 0.9998 | | 0.0003 | 0.88 | 4180 | 0.0034 | 0.9993 | | 0.0002 | 0.96 | 4560 | 0.0017 | 0.9993 | ### Framework versions - Transformers 4.43.3 - Pytorch 2.3.1+cu121 - Datasets 2.14.4 - Tokenizers 0.19.1