update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- source_data
+metrics:
+- precision
+- recall
+- f1
+model-index:
+- name: SourceData_GENEPROD-ROLES_v_2-0-2_BioLinkBERT_large
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: source_data
+      type: source_data
+      args: ROLES_GP
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9246803900325027
+    - name: Recall
+      type: recall
+      value: 0.9319095038434662
+    - name: F1
+      type: f1
+      value: 0.9282808727241086
+---
+
+<!-- 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. -->
+
+# SourceData_GENEPROD-ROLES_v_2-0-2_BioLinkBERT_large
+
+This model is a fine-tuned version of [michiyasunaga/BioLinkBERT-large](https://huggingface.co/michiyasunaga/BioLinkBERT-large) on the source_data dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0136
+- Accuracy Score: 0.9952
+- Precision: 0.9247
+- Recall: 0.9319
+- F1: 0.9283
+
+## 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: 1e-05
+- train_batch_size: 32
+- eval_batch_size: 256
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 64
+- optimizer: Adafactor
+- lr_scheduler_type: linear
+- num_epochs: 1.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy Score | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------------:|:---------:|:------:|:------:|
+| 0.0154        | 1.0   | 942  | 0.0136          | 0.9952         | 0.9247    | 0.9319 | 0.9283 |
+
+
+### Framework versions
+
+- Transformers 4.20.1
+- Pytorch 1.11.0a0+bfe5ad2
+- Datasets 2.10.1
+- Tokenizers 0.12.1