End of training

README.md

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+---
+library_name: transformers
+base_model: raulgdp/xml-roberta-large-finetuned-ner
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: xml-roberta-large-finetuned-ner-finetuned-ner
+  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. -->
+
+# xml-roberta-large-finetuned-ner-finetuned-ner
+
+This model is a fine-tuned version of [raulgdp/xml-roberta-large-finetuned-ner](https://huggingface.co/raulgdp/xml-roberta-large-finetuned-ner) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0847
+- Precision: 0.9493
+- Recall: 0.9728
+- F1: 0.9609
+- Accuracy: 0.9815
+
+## 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 adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 200
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.5713        | 1.0   | 612  | 0.1009          | 0.9281    | 0.9603 | 0.9439 | 0.9729   |
+| 0.1048        | 2.0   | 1224 | 0.0903          | 0.9350    | 0.9730 | 0.9536 | 0.9779   |
+| 0.0743        | 3.0   | 1836 | 0.0783          | 0.9520    | 0.9745 | 0.9631 | 0.9823   |
+| 0.0568        | 4.0   | 2448 | 0.0855          | 0.9474    | 0.9712 | 0.9591 | 0.9802   |
+| 0.0361        | 5.0   | 3060 | 0.0847          | 0.9493    | 0.9728 | 0.9609 | 0.9815   |
+
+
+### Framework versions
+
+- Transformers 4.46.3
+- Pytorch 2.5.1+cu121
+- Datasets 3.1.0
+- Tokenizers 0.20.3

model.safetensors

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