update model card README.md

README.md

@@ -0,0 +1,78 @@
+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-base-cased-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-cased-ner
+
+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: 0.3793
+- Job Title precision: 0.8079
+- Job Title recall: 0.8248
+- Job Title f1: 0.8163
+- Loc precision: 0.8911
+- Loc recall: 0.9081
+- Loc f1: 0.8995
+- Org precision: 0.6484
+- Org recall: 0.7620
+- Org f1: 0.7006
+- Misc precision: 0.6134
+- Misc recall: 0.7201
+- Misc f1: 0.6625
+- Precision: 0.7800
+- Recall: 0.8265
+- F1: 0.8025
+- Accuracy: 0.8606
+
+## 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: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Job Title precision | Job Title recall | Job Title f1 | Loc precision | Loc recall | Loc f1 | Org precision | Org recall | Org f1 | Misc precision | Misc recall | Misc f1 | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:-------------------:|:----------------:|:------------:|:-------------:|:----------:|:------:|:-------------:|:----------:|:------:|:--------------:|:-----------:|:-------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 308  | 0.3793          | 0.8079              | 0.8248           | 0.8163       | 0.8911        | 0.9081     | 0.8995 | 0.6484        | 0.7620     | 0.7006 | 0.6134         | 0.7201      | 0.6625  | 0.7800    | 0.8265 | 0.8025 | 0.8606   |
+| 0.4249        | 2.0   | 616  | 0.3866          | 0.7911              | 0.8728           | 0.8299       | 0.8676        | 0.9541     | 0.9088 | 0.6551        | 0.7886     | 0.7157 | 0.6623         | 0.6962      | 0.6789  | 0.7719    | 0.8669 | 0.8167 | 0.8685   |
+
+
+### Framework versions
+
+- Transformers 4.28.1
+- Pytorch 1.7.1+cu110
+- Datasets 2.12.0
+- Tokenizers 0.13.2