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: polyglot-tagger-v2.2
+  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. -->
+
+# polyglot-tagger-v2.2
+
+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: 0.0345
+- Precision: 0.9508
+- Recall: 0.9647
+- F1: 0.9577
+- Accuracy: 0.9908
+
+## 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: 18
+- eval_batch_size: 18
+- seed: 42
+- gradient_accumulation_steps: 8
+- 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 |
+|:-------------:|:------:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.3393        | 0.0804 | 2500  | 0.1078          | 0.7999    | 0.8817 | 0.8388 | 0.9723   |
+| 0.3042        | 0.1609 | 5000  | 0.0910          | 0.8422    | 0.9054 | 0.8726 | 0.9766   |
+| 0.2323        | 0.2413 | 7500  | 0.0859          | 0.8661    | 0.9174 | 0.8910 | 0.9766   |
+| 0.2253        | 0.3218 | 10000 | 0.0707          | 0.8805    | 0.9266 | 0.9029 | 0.9818   |
+| 0.2117        | 0.4022 | 12500 | 0.0715          | 0.8943    | 0.9284 | 0.9110 | 0.9805   |
+| 0.1895        | 0.4827 | 15000 | 0.0582          | 0.8992    | 0.9372 | 0.9178 | 0.9843   |
+| 0.1865        | 0.5631 | 17500 | 0.0557          | 0.9053    | 0.9381 | 0.9214 | 0.9851   |
+| 0.1666        | 0.6436 | 20000 | 0.0560          | 0.9047    | 0.9424 | 0.9232 | 0.9852   |
+| 0.1623        | 0.7240 | 22500 | 0.0588          | 0.9099    | 0.9405 | 0.9250 | 0.9838   |
+| 0.1564        | 0.8045 | 25000 | 0.0476          | 0.9232    | 0.9489 | 0.9359 | 0.9872   |
+| 0.1474        | 0.8849 | 27500 | 0.0525          | 0.9200    | 0.9483 | 0.9339 | 0.9855   |
+| 0.1580        | 0.9654 | 30000 | 0.0455          | 0.9245    | 0.9502 | 0.9372 | 0.9878   |
+| 0.1245        | 1.0458 | 32500 | 0.0447          | 0.9310    | 0.9536 | 0.9422 | 0.9881   |
+| 0.1199        | 1.1262 | 35000 | 0.0445          | 0.9316    | 0.9547 | 0.9430 | 0.9881   |
+| 0.1093        | 1.2067 | 37500 | 0.0432          | 0.9363    | 0.9559 | 0.9460 | 0.9886   |
+| 0.1164        | 1.2871 | 40000 | 0.0410          | 0.9392    | 0.9583 | 0.9487 | 0.9895   |
+| 0.1146        | 1.3676 | 42500 | 0.0433          | 0.9314    | 0.9562 | 0.9436 | 0.9886   |
+| 0.0913        | 1.4480 | 45000 | 0.0434          | 0.9403    | 0.9585 | 0.9493 | 0.9894   |
+| 0.1068        | 1.5285 | 47500 | 0.0397          | 0.9424    | 0.9608 | 0.9515 | 0.9897   |
+| 0.0930        | 1.6089 | 50000 | 0.0388          | 0.9419    | 0.9605 | 0.9511 | 0.9898   |
+| 0.0896        | 1.6894 | 52500 | 0.0371          | 0.9453    | 0.9623 | 0.9537 | 0.9901   |
+| 0.0862        | 1.7698 | 55000 | 0.0362          | 0.9446    | 0.9624 | 0.9534 | 0.9903   |
+| 0.0971        | 1.8503 | 57500 | 0.0355          | 0.9478    | 0.9635 | 0.9556 | 0.9908   |
+| 0.0947        | 1.9307 | 60000 | 0.0345          | 0.9508    | 0.9647 | 0.9577 | 0.9908   |
+
+
+### 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>"
+}