update model card README.md

README.md

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+---
+license: cc-by-nc-sa-4.0
+tags:
+- generated_from_trainer
+datasets:
+- skript
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: wikineural-multilingual-ner-finetuned-ner
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: skript
+      type: skript
+      config: myscript
+      split: train
+      args: myscript
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9007335298553506
+    - name: Recall
+      type: recall
+      value: 0.9301946902654867
+    - name: F1
+      type: f1
+      value: 0.9152270827528559
+    - name: Accuracy
+      type: accuracy
+      value: 0.9653644982020269
+---
+
+<!-- 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. -->
+
+# wikineural-multilingual-ner-finetuned-ner
+
+This model is a fine-tuned version of [Babelscape/wikineural-multilingual-ner](https://huggingface.co/Babelscape/wikineural-multilingual-ner) on the skript dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1243
+- Precision: 0.9007
+- Recall: 0.9302
+- F1: 0.9152
+- Accuracy: 0.9654
+
+## 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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 298  | 0.1179          | 0.8975    | 0.8981 | 0.8978 | 0.9592   |
+| 0.104         | 2.0   | 596  | 0.1161          | 0.9051    | 0.9201 | 0.9126 | 0.9648   |
+| 0.104         | 3.0   | 894  | 0.1243          | 0.9007    | 0.9302 | 0.9152 | 0.9654   |
+
+
+### Framework versions
+
+- Transformers 4.21.0
+- Pytorch 1.12.0+cu113
+- Datasets 2.4.0
+- Tokenizers 0.12.1