End of training

README.md

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+---
+language:
+- en
+license: apache-2.0
+datasets:
+- conll2003
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-large-uncased
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: conll2003
+      type: conll2003
+      args: default
+    metrics:
+    - name: precision
+      type: precision
+      value: 0.9504719600222099
+    - name: recall
+      type: recall
+      value: 0.9574896520863632
+    - name: f1
+      type: f1
+      value: 0.9539679001337494
+    - name: accuracy
+      type: accuracy
+      value: 0.9885618059637473
+---
+
+<!-- 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-uncased
+
+This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the conll2003 dataset.
+It achieves the following results on the evaluation set:
+- precision: 0.9505
+- recall: 0.9575
+- f1: 0.9540
+- accuracy: 0.9886
+
+## 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:
+- num_train_epochs: 10
+- train_batch_size: 4
+- learning_rate: 2e-05
+- weight_decay_rate: 0.01
+- num_warmup_steps: 0
+- fp16: True
+
+### Framework versions
+
+- Transformers 4.16.2
+- Pytorch 1.8.1+cu111
+- Datasets 1.18.3
+- Tokenizers 0.11.0

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