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_coarse-ner
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: lextreme
+      type: lextreme
+      config: mapa_coarse
+      split: test
+      args: mapa_coarse
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.7191116088092572
+    - name: Recall
+      type: recall
+      value: 0.6452855468095796
+    - name: F1
+      type: f1
+      value: 0.6802012534204254
+    - name: Accuracy
+      type: accuracy
+      value: 0.9878756336348935
+---
+
+<!-- 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_coarse-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: 0.0882
+- Precision: 0.7191
+- Recall: 0.6453
+- F1: 0.6802
+- Accuracy: 0.9879
+
+## 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0248        | 1.0   | 1739  | 0.0528          | 0.7451    | 0.5805 | 0.6525 | 0.9871   |
+| 0.0181        | 2.0   | 3478  | 0.0595          | 0.7369    | 0.5749 | 0.6459 | 0.9875   |
+| 0.0121        | 3.0   | 5217  | 0.0499          | 0.7404    | 0.6280 | 0.6796 | 0.9879   |
+| 0.0088        | 4.0   | 6956  | 0.0634          | 0.6912    | 0.6334 | 0.6610 | 0.9875   |
+| 0.0072        | 5.0   | 8695  | 0.0625          | 0.7109    | 0.6478 | 0.6779 | 0.9880   |
+| 0.0052        | 6.0   | 10434 | 0.0702          | 0.7098    | 0.6518 | 0.6796 | 0.9878   |
+| 0.0041        | 7.0   | 12173 | 0.0733          | 0.7176    | 0.6429 | 0.6782 | 0.9878   |
+| 0.0026        | 8.0   | 13912 | 0.0779          | 0.7198    | 0.6540 | 0.6853 | 0.9879   |
+| 0.0019        | 9.0   | 15651 | 0.0875          | 0.7181    | 0.6419 | 0.6779 | 0.9877   |
+| 0.0018        | 10.0  | 17390 | 0.0882          | 0.7191    | 0.6453 | 0.6802 | 0.9879   |
+
+
+### Framework versions
+
+- Transformers 4.26.0
+- Pytorch 1.13.1+cu117
+- Datasets 2.9.0
+- Tokenizers 0.13.2