Model save

README.md

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+---
+library_name: transformers
+base_model: karakaka/segmentation-pydec-mlm
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: segmentation-pydec-segmenter
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# segmentation-pydec-segmenter
+
+This model is a fine-tuned version of [karakaka/segmentation-pydec-mlm](https://huggingface.co/karakaka/segmentation-pydec-mlm) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1817
+- Precision: 0.6660
+- Recall: 0.7669
+- F1: 0.7129
+- Accuracy: 0.9133
+
+## 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
+- num_devices: 8
+- total_train_batch_size: 384
+- total_eval_batch_size: 64
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.3276        | 1.0   | 883  | 0.2217          | 0.6299    | 0.7274 | 0.6752 | 0.8945   |
+| 0.2329        | 2.0   | 1766 | 0.1817          | 0.6660    | 0.7669 | 0.7129 | 0.9133   |
+
+
+### Framework versions
+
+- Transformers 4.46.1
+- Pytorch 2.7.1+cu126
+- Datasets 4.0.0
+- Tokenizers 0.20.3