update model card README.md

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- wikiann
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: BERTreach-finetuned-ner
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: wikiann
+      type: wikiann
+      args: ga
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.5200517464424321
+    - name: Recall
+      type: recall
+      value: 0.5667293233082706
+    - name: F1
+      type: f1
+      value: 0.5423881268270744
+    - name: Accuracy
+      type: accuracy
+      value: 0.8365605828220859
+---
+
+<!-- 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. -->
+
+# BERTreach-finetuned-ner
+
+This model is a fine-tuned version of [jimregan/BERTreach](https://huggingface.co/jimregan/BERTreach) on the wikiann dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4944
+- Precision: 0.5201
+- Recall: 0.5667
+- F1: 0.5424
+- Accuracy: 0.8366
+
+## 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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 63   | 0.7249          | 0.3645    | 0.3905 | 0.3770 | 0.7584   |
+| No log        | 2.0   | 126  | 0.5850          | 0.4529    | 0.4948 | 0.4729 | 0.8072   |
+| No log        | 3.0   | 189  | 0.5192          | 0.4949    | 0.5456 | 0.5190 | 0.8288   |
+| No log        | 4.0   | 252  | 0.5042          | 0.5208    | 0.5592 | 0.5393 | 0.8348   |
+| No log        | 5.0   | 315  | 0.4944          | 0.5201    | 0.5667 | 0.5424 | 0.8366   |
+
+
+### Framework versions
+
+- Transformers 4.12.5
+- Pytorch 1.10.0+cu111
+- Datasets 1.16.1
+- Tokenizers 0.10.3