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:
+- named-entity-recognition
+- hausa
+- african-language
+- pii-detection
+- token-classification
+- generated_from_trainer
+datasets:
+- Beijuka/Multilingual_PII_NER_dataset
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: multilingual-google-bert/bert-base-multilingual-cased-hausa-ner-v1
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: Beijuka/Multilingual_PII_NER_dataset
+      type: Beijuka/Multilingual_PII_NER_dataset
+      args: 'split: train+validation+test'
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9529745042492918
+    - name: Recall
+      type: recall
+      value: 0.9236683141131247
+    - name: F1
+      type: f1
+      value: 0.9380925822643614
+    - name: Accuracy
+      type: accuracy
+      value: 0.9788954787029192
+---
+
+<!-- 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. -->
+
+# multilingual-google-bert/bert-base-multilingual-cased-hausa-ner-v1
+
+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 Beijuka/Multilingual_PII_NER_dataset dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1237
+- Precision: 0.9530
+- Recall: 0.9237
+- F1: 0.9381
+- Accuracy: 0.9789
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- 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: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 301  | 0.1502          | 0.8451    | 0.8843 | 0.8643 | 0.9526   |
+| 0.2112        | 2.0   | 602  | 0.1347          | 0.8573    | 0.9393 | 0.8964 | 0.9604   |
+| 0.2112        | 3.0   | 903  | 0.1241          | 0.8813    | 0.9398 | 0.9096 | 0.9668   |
+| 0.0847        | 4.0   | 1204 | 0.1770          | 0.8589    | 0.9460 | 0.9004 | 0.9640   |
+| 0.0619        | 5.0   | 1505 | 0.1295          | 0.9012    | 0.9146 | 0.9078 | 0.9673   |
+| 0.0619        | 6.0   | 1806 | 0.1502          | 0.9018    | 0.9254 | 0.9134 | 0.9683   |
+| 0.0394        | 7.0   | 2107 | 0.1801          | 0.8729    | 0.9506 | 0.9101 | 0.9661   |
+| 0.0394        | 8.0   | 2408 | 0.1807          | 0.9119    | 0.9321 | 0.9219 | 0.9705   |
+| 0.0236        | 9.0   | 2709 | 0.1660          | 0.9259    | 0.9187 | 0.9223 | 0.9719   |
+| 0.0124        | 10.0  | 3010 | 0.1878          | 0.8939    | 0.9496 | 0.9209 | 0.9705   |
+| 0.0124        | 11.0  | 3311 | 0.2095          | 0.8874    | 0.9486 | 0.9170 | 0.9693   |
+| 0.01          | 12.0  | 3612 | 0.2370          | 0.8814    | 0.9480 | 0.9135 | 0.9664   |
+
+
+### Framework versions
+
+- Transformers 4.55.4
+- Pytorch 2.8.0+cu126
+- Datasets 4.0.0
+- Tokenizers 0.21.4

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