update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- lextreme
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: distilbert-base-multilingual-cased-mapa_fine-ner
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: lextreme
+      type: lextreme
+      config: mapa_fine
+      split: test
+      args: mapa_fine
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.8763335204941044
+    - name: Recall
+      type: recall
+      value: 0.9115199299167762
+    - name: F1
+      type: f1
+      value: 0.8935804766335075
+    - name: Accuracy
+      type: accuracy
+      value: 0.9956876979901592
+---
+
+<!-- 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. -->
+
+# distilbert-base-multilingual-cased-mapa_fine-ner
+
+This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the lextreme dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0282
+- Precision: 0.8763
+- Recall: 0.9115
+- F1: 0.8936
+- Accuracy: 0.9957
+
+## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0244        | 1.0   | 1739  | 0.0202          | 0.8083    | 0.9314 | 0.8655 | 0.9941   |
+| 0.0154        | 2.0   | 3478  | 0.0173          | 0.8813    | 0.9006 | 0.8908 | 0.9954   |
+| 0.0118        | 3.0   | 5217  | 0.0161          | 0.8885    | 0.9131 | 0.9006 | 0.9960   |
+| 0.0084        | 4.0   | 6956  | 0.0194          | 0.8485    | 0.9295 | 0.8871 | 0.9953   |
+| 0.0069        | 5.0   | 8695  | 0.0219          | 0.8583    | 0.9198 | 0.8880 | 0.9953   |
+| 0.0054        | 6.0   | 10434 | 0.0229          | 0.8622    | 0.9160 | 0.8883 | 0.9954   |
+| 0.0032        | 7.0   | 12173 | 0.0248          | 0.8817    | 0.8979 | 0.8898 | 0.9956   |
+| 0.0023        | 8.0   | 13912 | 0.0265          | 0.8900    | 0.9023 | 0.8961 | 0.9958   |
+| 0.0018        | 9.0   | 15651 | 0.0275          | 0.8657    | 0.9137 | 0.8890 | 0.9954   |
+| 0.0016        | 10.0  | 17390 | 0.0282          | 0.8763    | 0.9115 | 0.8936 | 0.9957   |
+
+
+### Framework versions
+
+- Transformers 4.26.0
+- Pytorch 1.13.1+cu117
+- Datasets 2.9.0
+- Tokenizers 0.13.2