| library_name: transformers | |
| base_model: syssec-utd/py36-pylingual-v1-mlm | |
| tags: | |
| - generated_from_trainer | |
| metrics: | |
| - precision | |
| - recall | |
| - f1 | |
| - accuracy | |
| model-index: | |
| - name: py36-pylingual-v1-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. --> | |
| # py36-pylingual-v1-segmenter | |
| This model is a fine-tuned version of [syssec-utd/py36-pylingual-v1-mlm](https://huggingface.co/syssec-utd/py36-pylingual-v1-mlm) on the syssec-utd/segmentation-py36-pylingual-v1-tokenized dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.0006 | |
| - Precision: 1.0 | |
| - Recall: 1.0 | |
| - F1: 1.0 | |
| - Accuracy: 1.0 | |
| ## 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: 48 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - distributed_type: multi-GPU | |
| - 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: 2 | |
| - mixed_precision_training: Native AMP | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | | |
| |:-------------:|:-----:|:------:|:---------------:|:---------:|:------:|:---:|:--------:| | |
| | 0.0051 | 1.0 | 90840 | 0.0014 | 1.0 | 1.0 | 1.0 | 1.0 | | |
| | 0.0029 | 2.0 | 181680 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 | | |
| ### Framework versions | |
| - Transformers 4.48.2 | |
| - Pytorch 2.4.1+cu121 | |
| - Datasets 3.0.1 | |
| - Tokenizers 0.21.0 | |