update model card README.md

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- ncbi_disease
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: electramed-small-NCBI-ner
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: ncbi_disease
+      type: ncbi_disease
+      config: ncbi_disease
+      split: train
+      args: ncbi_disease
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.8083491461100569
+    - name: Recall
+      type: recall
+      value: 0.8875
+    - name: F1
+      type: f1
+      value: 0.846077457795432
+    - name: Accuracy
+      type: accuracy
+      value: 0.9820794382985671
+---
+
+<!-- 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. -->
+
+# electramed-small-NCBI-ner
+
+This model is a fine-tuned version of [giacomomiolo/electramed_small_scivocab](https://huggingface.co/giacomomiolo/electramed_small_scivocab) on the ncbi_disease dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0664
+- Precision: 0.8083
+- Recall: 0.8875
+- F1: 0.8461
+- Accuracy: 0.9821
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.4787        | 1.0   | 340  | 0.5090          | 0.6090    | 0.5062 | 0.5529 | 0.9608   |
+| 0.2029        | 2.0   | 680  | 0.1890          | 0.7643    | 0.8208 | 0.7916 | 0.9774   |
+| 0.1402        | 3.0   | 1020 | 0.1106          | 0.7839    | 0.8802 | 0.8292 | 0.9807   |
+| 0.075         | 4.0   | 1360 | 0.0876          | 0.8162    | 0.8698 | 0.8422 | 0.9817   |
+| 0.0408        | 5.0   | 1700 | 0.0776          | 0.8090    | 0.8781 | 0.8422 | 0.9818   |
+| 0.0308        | 6.0   | 2040 | 0.0697          | 0.8044    | 0.8823 | 0.8415 | 0.9825   |
+| 0.0405        | 7.0   | 2380 | 0.0680          | 0.8118    | 0.8854 | 0.8470 | 0.9830   |
+| 0.0138        | 8.0   | 2720 | 0.0665          | 0.8111    | 0.8854 | 0.8466 | 0.9826   |
+| 0.0223        | 9.0   | 3060 | 0.0675          | 0.8064    | 0.8896 | 0.8460 | 0.9821   |
+| 0.0395        | 10.0  | 3400 | 0.0664          | 0.8083    | 0.8875 | 0.8461 | 0.9821   |
+
+
+### Framework versions
+
+- Transformers 4.21.1
+- Pytorch 1.12.1+cu113
+- Datasets 2.4.0
+- Tokenizers 0.12.1