update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-finetuned-ner-ime
+  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-finetuned-ner-ime
+
+This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.4592
+- Precision: 0.6456
+- Recall: 0.3813
+- F1: 0.4794
+- Accuracy: 0.6108
+
+## 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: 8
+- eval_batch_size: 8
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 221  | 2.6044          | 0.6263    | 0.3774 | 0.4710 | 0.6081   |
+| No log        | 2.0   | 442  | 2.5040          | 0.6286    | 0.3848 | 0.4774 | 0.6100   |
+| 2.7612        | 3.0   | 663  | 2.4592          | 0.6456    | 0.3813 | 0.4794 | 0.6108   |
+
+
+### Framework versions
+
+- Transformers 4.28.0
+- Pytorch 2.0.1
+- Datasets 2.12.0
+- Tokenizers 0.11.0