update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- token-classification
+- generated_from_trainer
+datasets:
+- source_data
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-large-cased-lora-finetuned-ner-EMBO-SourceData
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: source_data
+      type: source_data
+      config: NER
+      split: test
+      args: NER
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.7998649706157647
+    - name: Recall
+      type: recall
+      value: 0.827835919261859
+    - name: F1
+      type: f1
+      value: 0.8136101139378804
+    - name: Accuracy
+      type: accuracy
+      value: 0.9583887230224973
+---
+
+<!-- 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. -->
+
+# bert-large-cased-lora-finetuned-ner-EMBO-SourceData
+
+This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on the source_data dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1282
+- Precision: 0.7999
+- Recall: 0.8278
+- F1: 0.8136
+- Accuracy: 0.9584
+
+## 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: 0.001
+- 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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.1552        | 1.0   | 3454  | 0.1499          | 0.7569    | 0.7968 | 0.7763 | 0.9516   |
+| 0.1179        | 2.0   | 6908  | 0.1328          | 0.7910    | 0.8120 | 0.8013 | 0.9564   |
+| 0.0998        | 3.0   | 10362 | 0.1282          | 0.7999    | 0.8278 | 0.8136 | 0.9584   |
+
+
+### Framework versions
+
+- Transformers 4.26.1
+- Pytorch 2.0.1
+- Datasets 2.13.1
+- Tokenizers 0.13.3