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README.md
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---
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library_name: transformers
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base_model: syssec-utd/py315-pylingual-v2-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: py315-pylingual-v2-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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# py315-pylingual-v2-segmenter
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This model is a fine-tuned version of [syssec-utd/py315-pylingual-v2-mlm](https://huggingface.co/syssec-utd/py315-pylingual-v2-mlm) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0066
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- Precision: 0.9910
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- Recall: 0.9917
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- F1: 0.9913
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- Accuracy: 0.9977
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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: 28
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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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- 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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| 0.0085 | 1.0 | 74922 | 0.0066 | 0.9905 | 0.9912 | 0.9908 | 0.9976 |
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| 0.0041 | 2.0 | 149844 | 0.0066 | 0.9910 | 0.9917 | 0.9913 | 0.9977 |
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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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