Model save

README.md

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+---
+library_name: transformers
+license: mit
+base_model: xlm-roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: BanglaHealthNER-Model
+  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. -->
+
+# BanglaHealthNER-Model
+
+This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2746
+- Precision: 0.5479
+- Recall: 0.6205
+- F1: 0.5820
+- Accuracy: 0.9011
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- 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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.292         | 1.0   | 1590 | 0.2948          | 0.4976    | 0.5848 | 0.5377 | 0.8906   |
+| 0.2538        | 2.0   | 3180 | 0.2741          | 0.5447    | 0.5948 | 0.5687 | 0.9005   |
+| 0.231         | 3.0   | 4770 | 0.2746          | 0.5479    | 0.6205 | 0.5820 | 0.9011   |
+
+
+### Framework versions
+
+- Transformers 4.53.3
+- Pytorch 2.6.0+cu124
+- Datasets 4.1.1
+- Tokenizers 0.21.2