End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: FacebookAI/xlm-roberta-large
+tags:
+- generated_from_trainer
+datasets:
+- conll2002
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: xlm-roberta-large-finetuned-ner
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: conll2002
+      type: conll2002
+      config: es
+      split: validation
+      args: es
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.86443345323741
+    - name: Recall
+      type: recall
+      value: 0.8835018382352942
+    - name: F1
+      type: f1
+      value: 0.8738636363636364
+    - name: Accuracy
+      type: accuracy
+      value: 0.9787686065955755
+---
+
+<!-- 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. -->
+
+# xlm-roberta-large-finetuned-ner
+
+This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the conll2002 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0973
+- Precision: 0.8644
+- Recall: 0.8835
+- F1: 0.8739
+- Accuracy: 0.9788
+
+## 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
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.1382        | 1.0   | 521  | 0.0906          | 0.8502    | 0.8830 | 0.8663 | 0.9782   |
+| 0.048         | 2.0   | 1042 | 0.0861          | 0.8472    | 0.8729 | 0.8599 | 0.9780   |
+| 0.0294        | 3.0   | 1563 | 0.0973          | 0.8644    | 0.8835 | 0.8739 | 0.9788   |
+
+
+### Framework versions
+
+- Transformers 4.46.3
+- Pytorch 2.5.1
+- Datasets 3.1.0
+- Tokenizers 0.20.3

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