End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google-bert/bert-base-uncased
+tags:
+- generated_from_trainer
+datasets:
+- conll2002
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: NER-finetuning-BETO-PRO
+  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: 0.7017726798748697
+    - name: Recall
+      type: recall
+      value: 0.7732077205882353
+    - name: F1
+      type: f1
+      value: 0.7357603585875151
+    - name: Accuracy
+      type: accuracy
+      value: 0.9536327652922068
+---
+
+<!-- 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-BETO-PRO
+
+This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the conll2002 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1981
+- Precision: 0.7018
+- Recall: 0.7732
+- F1: 0.7358
+- Accuracy: 0.9536
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.1941        | 1.0   | 1041 | 0.1965          | 0.6201    | 0.6836 | 0.6503 | 0.9422   |
+| 0.1276        | 2.0   | 2082 | 0.1843          | 0.6666    | 0.7387 | 0.7008 | 0.9487   |
+| 0.0885        | 3.0   | 3123 | 0.1760          | 0.7056    | 0.7601 | 0.7319 | 0.9538   |
+| 0.0623        | 4.0   | 4164 | 0.1856          | 0.6982    | 0.7670 | 0.7310 | 0.9532   |
+| 0.0485        | 5.0   | 5205 | 0.1981          | 0.7018    | 0.7732 | 0.7358 | 0.9536   |
+
+
+### Framework versions
+
+- Transformers 4.50.3
+- Pytorch 2.6.0+cu124
+- Datasets 3.5.0
+- Tokenizers 0.21.1