End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google-bert/bert-base-multilingual-cased
+tags:
+- generated_from_trainer
+datasets:
+- conll2002
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: NER-finetuning-Bert-base
+  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: 0.8351917930419268
+    - name: Recall
+      type: recall
+      value: 0.8605238970588235
+    - name: F1
+      type: f1
+      value: 0.8476686283386147
+    - name: Accuracy
+      type: accuracy
+      value: 0.9714759394660772
+---
+
+<!-- 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. -->
+
+# NER-finetuning-Bert-base
+
+This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the conll2002 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1521
+- Precision: 0.8352
+- Recall: 0.8605
+- F1: 0.8477
+- Accuracy: 0.9715
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Use OptimizerNames.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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0855        | 1.0   | 1041 | 0.1281          | 0.8272    | 0.8371 | 0.8321 | 0.9688   |
+| 0.0536        | 2.0   | 2082 | 0.1357          | 0.8134    | 0.8465 | 0.8296 | 0.9686   |
+| 0.0333        | 3.0   | 3123 | 0.1227          | 0.8593    | 0.8713 | 0.8653 | 0.9740   |
+| 0.0221        | 4.0   | 4164 | 0.1482          | 0.8474    | 0.8564 | 0.8519 | 0.9710   |
+| 0.0163        | 5.0   | 5205 | 0.1521          | 0.8352    | 0.8605 | 0.8477 | 0.9715   |
+
+
+### Framework versions
+
+- Transformers 4.51.3
+- Pytorch 2.6.0+cu124
+- Datasets 3.5.1
+- Tokenizers 0.21.1