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--- |
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library_name: transformers |
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base_model: syssec-utd/py314-pylingual-v3-mlm |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: py314-pylingual-v3-segmenter |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# py314-pylingual-v3-segmenter |
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This model is a fine-tuned version of [syssec-utd/py314-pylingual-v3-mlm](https://huggingface.co/syssec-utd/py314-pylingual-v3-mlm) on the syssec-utd/segmentation-py314-pylingual-v3-tokenized dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0069 |
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- Precision: 0.9918 |
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- Recall: 0.9848 |
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- F1: 0.9883 |
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- Accuracy: 0.9968 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 48 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 3 |
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- total_train_batch_size: 144 |
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- total_eval_batch_size: 24 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 2 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.0068 | 1.0 | 44197 | 0.0076 | 0.9903 | 0.9772 | 0.9837 | 0.9959 | |
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| 0.0039 | 2.0 | 88394 | 0.0069 | 0.9918 | 0.9848 | 0.9883 | 0.9968 | |
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### Framework versions |
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- Transformers 4.57.3 |
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- Pytorch 2.9.1+cu128 |
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- Datasets 4.4.1 |
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- Tokenizers 0.22.1 |
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