update model card README.md

README.md

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+---
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: biobert-base-cased-v1.2-finetuned-ner-CRAFT_Augmented_EN-finetuned-ner-CRAFT_Augmented_EN
+  results: []
+---
+
+<!-- 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. -->
+
+# biobert-base-cased-v1.2-finetuned-ner-CRAFT_Augmented_EN-finetuned-ner-CRAFT_Augmented_EN
+
+This model is a fine-tuned version of [StivenLancheros/biobert-base-cased-v1.2-finetuned-ner-CRAFT_Augmented_EN](https://huggingface.co/StivenLancheros/biobert-base-cased-v1.2-finetuned-ner-CRAFT_Augmented_EN) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2213
+- Precision: 0.8528
+- Recall: 0.8617
+- F1: 0.8572
+- Accuracy: 0.9709
+
+## 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: 3e-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: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0106        | 1.0   | 1360 | 0.1866          | 0.8343    | 0.8661 | 0.8499 | 0.9698   |
+| 0.0063        | 2.0   | 2720 | 0.2100          | 0.8536    | 0.8537 | 0.8537 | 0.9701   |
+| 0.0031        | 3.0   | 4080 | 0.2133          | 0.8506    | 0.8578 | 0.8542 | 0.9705   |
+| 0.0008        | 4.0   | 5440 | 0.2213          | 0.8528    | 0.8617 | 0.8572 | 0.9709   |
+
+
+### Framework versions
+
+- Transformers 4.17.0
+- Pytorch 1.10.0+cu111
+- Datasets 2.0.0
+- Tokenizers 0.11.6