update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- conll2003
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-base-uncased-finetuned-ner
+  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. -->
+
+# bert-base-uncased-finetuned-ner
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the conll2003 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0712
+- Precision: 0.8945
+- Recall: 0.9182
+- F1: 0.9062
+- Accuracy: 0.9793
+
+## 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: 1
+- eval_batch_size: 1
+- seed: 42
+- distributed_type: IPU
+- gradient_accumulation_steps: 16
+- total_train_batch_size: 64
+- total_eval_batch_size: 20
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+- training precision: Mixed Precision
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.1318        | 1.0   | 219  | 0.0967          | 0.8371    | 0.8714 | 0.8539 | 0.9705   |
+| 0.0597        | 2.0   | 438  | 0.0735          | 0.8912    | 0.9052 | 0.8981 | 0.9779   |
+| 0.0523        | 3.0   | 657  | 0.0712          | 0.8945    | 0.9182 | 0.9062 | 0.9793   |
+
+
+### Framework versions
+
+- Transformers 4.20.0
+- Pytorch 1.10.0+cpu
+- Datasets 2.4.0
+- Tokenizers 0.12.1