Model save

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
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+tokenizer.json filter=lfs diff=lfs merge=lfs -text

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: lang-ner-xlmr
+  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. -->
+
+# lang-ner-xlmr
+
+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: 0.0452
+- Precision: 0.8626
+- Recall: 0.8916
+- F1: 0.8769
+- Accuracy: 0.9892
+
+## 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: 5e-05
+- train_batch_size: 72
+- eval_batch_size: 36
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 144
+- 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 |
+|:-------------:|:------:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0730        | 0.0905 | 2500  | 0.1081          | 0.7241    | 0.8260 | 0.7717 | 0.9760   |
+| 0.0622        | 0.1809 | 5000  | 0.1276          | 0.6822    | 0.8122 | 0.7416 | 0.9724   |
+| 0.0556        | 0.2714 | 7500  | 0.0826          | 0.7701    | 0.8463 | 0.8064 | 0.9813   |
+| 0.0504        | 0.3618 | 10000 | 0.0763          | 0.7916    | 0.8562 | 0.8226 | 0.9822   |
+| 0.0480        | 0.4523 | 12500 | 0.0703          | 0.8025    | 0.8602 | 0.8304 | 0.9839   |
+| 0.0408        | 0.5427 | 15000 | 0.0750          | 0.8072    | 0.8637 | 0.8345 | 0.9837   |
+| 0.0443        | 0.6332 | 17500 | 0.0652          | 0.8149    | 0.8657 | 0.8395 | 0.9849   |
+| 0.0403        | 0.7236 | 20000 | 0.0647          | 0.8298    | 0.8728 | 0.8507 | 0.9859   |
+| 0.0413        | 0.8141 | 22500 | 0.0590          | 0.8253    | 0.8686 | 0.8464 | 0.9865   |
+| 0.0367        | 0.9045 | 25000 | 0.0582          | 0.8288    | 0.8743 | 0.8510 | 0.9867   |
+| 0.0395        | 0.9950 | 27500 | 0.0583          | 0.8304    | 0.8768 | 0.8530 | 0.9862   |
+| 0.0338        | 1.0854 | 30000 | 0.0567          | 0.8353    | 0.8783 | 0.8562 | 0.9869   |
+| 0.0291        | 1.1759 | 32500 | 0.0537          | 0.8443    | 0.8786 | 0.8611 | 0.9878   |
+| 0.0300        | 1.2663 | 35000 | 0.0521          | 0.8435    | 0.8805 | 0.8616 | 0.9878   |
+| 0.0269        | 1.3568 | 37500 | 0.0531          | 0.8515    | 0.8859 | 0.8683 | 0.9879   |
+| 0.0295        | 1.4472 | 40000 | 0.0517          | 0.8548    | 0.8882 | 0.8712 | 0.9882   |
+| 0.0279        | 1.5377 | 42500 | 0.0489          | 0.8550    | 0.8884 | 0.8714 | 0.9884   |
+| 0.0281        | 1.6281 | 45000 | 0.0480          | 0.8551    | 0.8875 | 0.8710 | 0.9887   |
+| 0.0277        | 1.7186 | 47500 | 0.0467          | 0.8605    | 0.8904 | 0.8752 | 0.9888   |
+| 0.0289        | 1.8090 | 50000 | 0.0458          | 0.8599    | 0.8919 | 0.8756 | 0.9892   |
+| 0.0268        | 1.8995 | 52500 | 0.0457          | 0.8623    | 0.8906 | 0.8762 | 0.9891   |
+| 0.0306        | 1.9899 | 55000 | 0.0452          | 0.8626    | 0.8916 | 0.8769 | 0.9892   |
+
+
+### Framework versions
+
+- Transformers 5.0.0
+- Pytorch 2.10.0+cu128
+- Datasets 4.0.0
+- Tokenizers 0.22.2

model.safetensors

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tokenizer.json

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tokenizer_config.json

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+{
+  "add_prefix_space": true,
+  "backend": "tokenizers",
+  "bos_token": "<s>",
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "is_local": false,
+  "mask_token": "<mask>",
+  "model_max_length": 512,
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "tokenizer_class": "XLMRobertaTokenizer",
+  "unk_token": "<unk>"
+}