--- library_name: transformers license: apache-2.0 base_model: bhadresh-savani/bert-base-uncased-emotion tags: - generated_from_trainer model-index: - name: BERT-Base-SE2025T11A-eng-v0.5 results: [] --- # BERT-Base-SE2025T11A-eng-v0.5 This model is a fine-tuned version of [bhadresh-savani/bert-base-uncased-emotion](https://huggingface.co/bhadresh-savani/bert-base-uncased-emotion) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.3877 - F1 Micro: 0.7444 - F1 Macro: 0.7028 - F1 Label Anger: 0.5570 - F1 Label Fear: 0.8087 - F1 Label Joy: 0.6915 - F1 Label Sad: 0.7317 - F1 Label Surprise: 0.725 ## 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: 2 - eval_batch_size: 2 - seed: 42 - optimizer: Use 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 | F1 Micro | F1 Macro | F1 Label Anger | F1 Label Fear | F1 Label Joy | F1 Label Sad | F1 Label Surprise | |:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:--------------:|:-------------:|:------------:|:------------:|:-----------------:| | 0.5761 | 0.1029 | 100 | 0.5207 | 0.5379 | 0.3482 | 0.0 | 0.7668 | 0.4559 | 0.0448 | 0.4737 | | 0.5062 | 0.2058 | 200 | 0.4711 | 0.6262 | 0.4402 | 0.0 | 0.7759 | 0.2783 | 0.6496 | 0.4974 | | 0.4609 | 0.3086 | 300 | 0.4505 | 0.6784 | 0.5705 | 0.2295 | 0.8 | 0.5860 | 0.6406 | 0.5962 | | 0.4421 | 0.4115 | 400 | 0.4639 | 0.6516 | 0.5346 | 0.1818 | 0.7792 | 0.5325 | 0.6352 | 0.5446 | | 0.4494 | 0.5144 | 500 | 0.4186 | 0.6535 | 0.5614 | 0.3235 | 0.8016 | 0.5967 | 0.5877 | 0.4974 | | 0.4368 | 0.6173 | 600 | 0.4234 | 0.6832 | 0.5650 | 0.1455 | 0.8110 | 0.6102 | 0.6753 | 0.5829 | | 0.4017 | 0.7202 | 700 | 0.4025 | 0.7185 | 0.6161 | 0.2105 | 0.8198 | 0.6602 | 0.6522 | 0.7376 | | 0.4394 | 0.8230 | 800 | 0.4114 | 0.7039 | 0.6192 | 0.4474 | 0.8049 | 0.4580 | 0.656 | 0.7295 | | 0.4148 | 0.9259 | 900 | 0.3776 | 0.7247 | 0.6752 | 0.5176 | 0.8109 | 0.6595 | 0.6723 | 0.7155 | | 0.3777 | 1.0288 | 1000 | 0.3775 | 0.7366 | 0.6860 | 0.5053 | 0.8136 | 0.6627 | 0.7170 | 0.7313 | | 0.2584 | 1.1317 | 1100 | 0.3924 | 0.7151 | 0.6459 | 0.4225 | 0.8106 | 0.6592 | 0.6280 | 0.7090 | | 0.2816 | 1.2346 | 1200 | 0.3764 | 0.7292 | 0.6561 | 0.3714 | 0.8166 | 0.6595 | 0.7016 | 0.7313 | | 0.2614 | 1.3374 | 1300 | 0.3825 | 0.7197 | 0.6533 | 0.3947 | 0.8106 | 0.6519 | 0.6667 | 0.7424 | | 0.2536 | 1.4403 | 1400 | 0.3899 | 0.7327 | 0.6702 | 0.3947 | 0.8057 | 0.6974 | 0.7097 | 0.7436 | | 0.2871 | 1.5432 | 1500 | 0.4037 | 0.7123 | 0.6396 | 0.4474 | 0.8182 | 0.5714 | 0.6824 | 0.6787 | | 0.2981 | 1.6461 | 1600 | 0.3986 | 0.7028 | 0.6392 | 0.4368 | 0.8211 | 0.6742 | 0.5556 | 0.7085 | | 0.2842 | 1.7490 | 1700 | 0.3978 | 0.7335 | 0.6627 | 0.4 | 0.828 | 0.6702 | 0.6840 | 0.7315 | | 0.2599 | 1.8519 | 1800 | 0.3968 | 0.7353 | 0.6761 | 0.4578 | 0.8357 | 0.6839 | 0.6803 | 0.7229 | | 0.2847 | 1.9547 | 1900 | 0.3981 | 0.7401 | 0.6706 | 0.4 | 0.8313 | 0.6845 | 0.6833 | 0.7538 | | 0.2298 | 2.0576 | 2000 | 0.4003 | 0.7214 | 0.6678 | 0.4773 | 0.8220 | 0.6736 | 0.7025 | 0.6635 | | 0.1892 | 2.1605 | 2100 | 0.4056 | 0.7396 | 0.6766 | 0.4471 | 0.8406 | 0.6667 | 0.7143 | 0.7143 | | 0.1665 | 2.2634 | 2200 | 0.4141 | 0.7352 | 0.6628 | 0.3836 | 0.8323 | 0.6809 | 0.6752 | 0.7422 | | 0.1565 | 2.3663 | 2300 | 0.4025 | 0.7342 | 0.6652 | 0.4211 | 0.8406 | 0.6514 | 0.6894 | 0.7236 | | 0.162 | 2.4691 | 2400 | 0.4134 | 0.72 | 0.6462 | 0.3889 | 0.8290 | 0.6629 | 0.6867 | 0.6636 | | 0.1689 | 2.5720 | 2500 | 0.4128 | 0.7366 | 0.6657 | 0.4110 | 0.8330 | 0.6667 | 0.7029 | 0.7149 | | 0.1588 | 2.6749 | 2600 | 0.4174 | 0.7373 | 0.6699 | 0.4267 | 0.8295 | 0.6667 | 0.7029 | 0.7236 | | 0.164 | 2.7778 | 2700 | 0.4122 | 0.7385 | 0.6721 | 0.4267 | 0.8343 | 0.6848 | 0.7004 | 0.7143 | | 0.2007 | 2.8807 | 2800 | 0.4115 | 0.7397 | 0.6728 | 0.4156 | 0.8357 | 0.6845 | 0.7004 | 0.7280 | | 0.1701 | 2.9835 | 2900 | 0.4133 | 0.7365 | 0.6695 | 0.4156 | 0.8347 | 0.6811 | 0.7 | 0.7160 | ### Framework versions - Transformers 4.46.0 - Pytorch 2.5.0+cu121 - Datasets 3.0.2 - Tokenizers 0.20.1