update model card README.md

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- bc2gm_corpus
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: electramed-small-BC2GM-ner
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: bc2gm_corpus
+      type: bc2gm_corpus
+      config: bc2gm_corpus
+      split: train
+      args: bc2gm_corpus
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.7652071701439906
+    - name: Recall
+      type: recall
+      value: 0.823399209486166
+    - name: F1
+      type: f1
+      value: 0.7932373771989948
+    - name: Accuracy
+      type: accuracy
+      value: 0.9756735092182762
+---
+
+<!-- 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-BC2GM-ner
+
+This model is a fine-tuned version of [giacomomiolo/electramed_small_scivocab](https://huggingface.co/giacomomiolo/electramed_small_scivocab) on the bc2gm_corpus dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0720
+- Precision: 0.7652
+- Recall: 0.8234
+- F1: 0.7932
+- Accuracy: 0.9757
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.085         | 1.0   | 782  | 0.1112          | 0.6147    | 0.7777 | 0.6867 | 0.9634   |
+| 0.0901        | 2.0   | 1564 | 0.0825          | 0.7141    | 0.8028 | 0.7559 | 0.9720   |
+| 0.0303        | 3.0   | 2346 | 0.0759          | 0.7310    | 0.8049 | 0.7662 | 0.9724   |
+| 0.0037        | 4.0   | 3128 | 0.0735          | 0.7430    | 0.8168 | 0.7781 | 0.9735   |
+| 0.0325        | 5.0   | 3910 | 0.0723          | 0.7571    | 0.8142 | 0.7846 | 0.9748   |
+| 0.0582        | 6.0   | 4692 | 0.0701          | 0.7664    | 0.8144 | 0.7897 | 0.9759   |
+| 0.0073        | 7.0   | 5474 | 0.0701          | 0.7711    | 0.8212 | 0.7953 | 0.9761   |
+| 0.1031        | 8.0   | 6256 | 0.0712          | 0.7602    | 0.8258 | 0.7916 | 0.9756   |
+| 0.0248        | 9.0   | 7038 | 0.0722          | 0.7691    | 0.8231 | 0.7952 | 0.9759   |
+| 0.0136        | 10.0  | 7820 | 0.0720          | 0.7652    | 0.8234 | 0.7932 | 0.9757   |
+
+
+### Framework versions
+
+- Transformers 4.22.1
+- Pytorch 1.12.1+cu113
+- Datasets 2.4.0
+- Tokenizers 0.12.1