py38-pylingual-v1-segmenter
This model is a fine-tuned version of syssec-utd/py38-pylingual-v1-mlm on the syssec-utd/segmentation-py38-pylingual-v1-tokenized dataset. It achieves the following results on the evaluation set:
- Loss: 0.0025
- Precision: 0.9968
- Recall: 0.9968
- F1: 0.9968
- Accuracy: 0.9992
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 |
|---|---|---|---|---|---|---|---|
| 0.0055 | 1.0 | 101234 | 0.0030 | 0.9956 | 0.9963 | 0.9959 | 0.9990 |
| 0.0032 | 2.0 | 202468 | 0.0025 | 0.9968 | 0.9968 | 0.9968 | 0.9992 |
Framework versions
- Transformers 4.48.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.0