update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- few_nerd
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: Cybonto-distilbert-base-uncased-finetuned-ner-FewNerd
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: few_nerd
+      type: few_nerd
+      args: supervised
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.7422259388187705
+    - name: Recall
+      type: recall
+      value: 0.7830368683449253
+    - name: F1
+      type: f1
+      value: 0.7620854216169805
+    - name: Accuracy
+      type: accuracy
+      value: 0.9386106950200795
+---
+
+<!-- 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. -->
+
+# Cybonto-distilbert-base-uncased-finetuned-ner-FewNerd
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the few_nerd dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2091
+- Precision: 0.7422
+- Recall: 0.7830
+- F1: 0.7621
+- Accuracy: 0.9386
+
+## 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: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.1964        | 1.0   | 4118  | 0.1946          | 0.7302    | 0.7761 | 0.7525 | 0.9366   |
+| 0.1685        | 2.0   | 8236  | 0.1907          | 0.7414    | 0.7776 | 0.7591 | 0.9384   |
+| 0.145         | 3.0   | 12354 | 0.1967          | 0.7454    | 0.7816 | 0.7631 | 0.9388   |
+| 0.1263        | 4.0   | 16472 | 0.2021          | 0.7402    | 0.7845 | 0.7617 | 0.9384   |
+| 0.1114        | 5.0   | 20590 | 0.2091          | 0.7422    | 0.7830 | 0.7621 | 0.9386   |
+
+
+### Framework versions
+
+- Transformers 4.18.0
+- Pytorch 1.10.0+cu111
+- Datasets 2.1.0
+- Tokenizers 0.12.1