update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+datasets:
+- wiki_neural
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-italian-finetuned-ner
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: wiki_neural
+      type: wiki_neural
+      config: it
+      split: validation
+      args: it
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9438064759036144
+    - name: Recall
+      type: recall
+      value: 0.954225352112676
+    - name: F1
+      type: f1
+      value: 0.9489873178118493
+    - name: Accuracy
+      type: accuracy
+      value: 0.9917883014379933
+---
+
+<!-- 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. -->
+
+# bert-italian-finetuned-ner
+
+This model is a fine-tuned version of [dbmdz/bert-base-italian-cased](https://huggingface.co/dbmdz/bert-base-italian-cased) on the wiki_neural dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0361
+- Precision: 0.9438
+- Recall: 0.9542
+- F1: 0.9490
+- Accuracy: 0.9918
+
+## 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: 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0297        | 1.0   | 11050 | 0.0323          | 0.9324    | 0.9420 | 0.9372 | 0.9908   |
+| 0.0173        | 2.0   | 22100 | 0.0324          | 0.9445    | 0.9514 | 0.9479 | 0.9915   |
+| 0.0057        | 3.0   | 33150 | 0.0361          | 0.9438    | 0.9542 | 0.9490 | 0.9918   |
+
+
+### Framework versions
+
+- Transformers 4.27.3
+- Pytorch 1.13.0
+- Datasets 2.1.0
+- Tokenizers 0.13.2