py313-pylingual-v3-segmenter
This model is a fine-tuned version of syssec-utd/py313-pylingual-v3-mlm on the syssec-utd/segmentation-py313-pylingual-v3-tokenized dataset. It achieves the following results on the evaluation set:
- Loss: 0.0047
- Precision: 0.9945
- Recall: 0.9944
- F1: 0.9945
- Accuracy: 0.9983
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 |
|---|---|---|---|---|---|---|---|
| 0.0073 | 1.0 | 99547 | 0.0049 | 0.9939 | 0.9938 | 0.9939 | 0.9981 |
| 0.0036 | 2.0 | 199094 | 0.0047 | 0.9945 | 0.9944 | 0.9945 | 0.9983 |
Framework versions
- Transformers 5.12.1
- Pytorch 2.12.0+cu130
- Datasets 5.0.0
- Tokenizers 0.22.2