metadata
library_name: transformers
base_model: syssec-utd/py314-pylingual-v6-mlm
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: py314-pylingual-v6-segmenter
results: []
py314-pylingual-v6-segmenter
This model is a fine-tuned version of syssec-utd/py314-pylingual-v6-mlm on the syssec-utd/segmentation-py314-pylingual-v6-tokenized dataset. It achieves the following results on the evaluation set:
- Loss: 0.0054
- Precision: 0.9930
- Recall: 0.9950
- F1: 0.9940
- 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 |
|---|---|---|---|---|---|---|---|
| 0.0062 | 1.0 | 183621 | 0.0043 | 0.9934 | 0.9948 | 0.9941 | 0.9983 |
| 0.0034 | 2.0 | 367242 | 0.0054 | 0.9930 | 0.9950 | 0.9940 | 0.9983 |
Framework versions
- Transformers 5.12.1
- Pytorch 2.12.0+cu130
- Datasets 5.0.0
- Tokenizers 0.22.2