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: 0.0427
+- Precision: 0.8949
+- Recall: 0.9144
+- F1: 0.9046
+- 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 |
+|:-------------:|:------:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0919        | 0.0894 | 2500  | 0.1243          | 0.7388    | 0.8336 | 0.7833 | 0.9712   |
+| 0.0798        | 0.1788 | 5000  | 0.0950          | 0.7928    | 0.8607 | 0.8254 | 0.9774   |
+| 0.0738        | 0.2682 | 7500  | 0.0857          | 0.8173    | 0.8722 | 0.8438 | 0.9785   |
+| 0.0611        | 0.3575 | 10000 | 0.0797          | 0.8247    | 0.8767 | 0.8499 | 0.9812   |
+| 0.0588        | 0.4469 | 12500 | 0.0732          | 0.8336    | 0.8843 | 0.8582 | 0.9822   |
+| 0.0542        | 0.5363 | 15000 | 0.0665          | 0.8560    | 0.8922 | 0.8737 | 0.9838   |
+| 0.0557        | 0.6257 | 17500 | 0.0613          | 0.8607    | 0.8949 | 0.8775 | 0.9845   |
+| 0.0486        | 0.7151 | 20000 | 0.0590          | 0.8567    | 0.8953 | 0.8755 | 0.9851   |
+| 0.0474        | 0.8045 | 22500 | 0.0601          | 0.8660    | 0.8971 | 0.8813 | 0.9854   |
+| 0.0545        | 0.8938 | 25000 | 0.0574          | 0.8675    | 0.9003 | 0.8836 | 0.9857   |
+| 0.0485        | 0.9832 | 27500 | 0.0566          | 0.8723    | 0.9018 | 0.8868 | 0.9858   |
+| 0.0440        | 1.0726 | 30000 | 0.0522          | 0.8769    | 0.9042 | 0.8904 | 0.9867   |
+| 0.0396        | 1.1620 | 32500 | 0.0509          | 0.8761    | 0.9046 | 0.8901 | 0.9873   |
+| 0.0383        | 1.2514 | 35000 | 0.0489          | 0.8788    | 0.9057 | 0.8921 | 0.9879   |
+| 0.0370        | 1.3408 | 37500 | 0.0486          | 0.8842    | 0.9087 | 0.8963 | 0.9877   |
+| 0.0350        | 1.4302 | 40000 | 0.0489          | 0.8769    | 0.9054 | 0.8909 | 0.9874   |
+| 0.0330        | 1.5195 | 42500 | 0.0478          | 0.8842    | 0.9091 | 0.8965 | 0.9879   |
+| 0.0308        | 1.6089 | 45000 | 0.0458          | 0.8897    | 0.9122 | 0.9008 | 0.9888   |
+| 0.0317        | 1.6983 | 47500 | 0.0454          | 0.8873    | 0.9114 | 0.8992 | 0.9887   |
+| 0.0322        | 1.7877 | 50000 | 0.0447          | 0.8900    | 0.9117 | 0.9007 | 0.9888   |
+| 0.0310        | 1.8771 | 52500 | 0.0439          | 0.8910    | 0.9126 | 0.9017 | 0.9888   |
+| 0.0294        | 1.9665 | 55000 | 0.0427          | 0.8949    | 0.9144 | 0.9046 | 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>"
+}