| library_name: transformers | |
| base_model: syssec-utd/py315-pylingual-v2-mlm | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - precision | |
| - recall | |
| - f1 | |
| - accuracy | |
| model-index: | |
| - name: py315-pylingual-v2-segmenter | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # py315-pylingual-v2-segmenter | |
| This model is a fine-tuned version of [syssec-utd/py315-pylingual-v2-mlm](https://huggingface.co/syssec-utd/py315-pylingual-v2-mlm) on the syssec-utd/segmentation-py315-pylingual-v2-tokenized dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.0066 | |
| - Precision: 0.9910 | |
| - Recall: 0.9917 | |
| - F1: 0.9913 | |
| - Accuracy: 0.9977 | |
| ## 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: 28 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - distributed_type: multi-GPU | |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments | |
| - lr_scheduler_type: linear | |
| - num_epochs: 2 | |
| - mixed_precision_training: Native AMP | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | | |
| |:-------------:|:-----:|:------:|:---------------:|:---------:|:------:|:------:|:--------:| | |
| | 0.0085 | 1.0 | 74922 | 0.0066 | 0.9905 | 0.9912 | 0.9908 | 0.9976 | | |
| | 0.0041 | 2.0 | 149844 | 0.0066 | 0.9910 | 0.9917 | 0.9913 | 0.9977 | | |
| ### Framework versions | |
| - Transformers 4.57.3 | |
| - Pytorch 2.9.1+cu128 | |
| - Datasets 4.4.1 | |
| - Tokenizers 0.22.1 | |