update model card README.md

README.md

@@ -0,0 +1,68 @@
+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-finetuned-cross-ner-v3
+  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-cross-ner-v3
+
+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: 0.1790
+- Precision: 0.8305
+- Recall: 0.8629
+- F1: 0.8464
+- Accuracy: 0.9559
+
+## 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
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.2023        | 1.0   | 2607 | 0.1921          | 0.7785    | 0.8197 | 0.7985 | 0.9468   |
+| 0.1244        | 2.0   | 5214 | 0.1740          | 0.8211    | 0.8541 | 0.8373 | 0.9547   |
+| 0.0792        | 3.0   | 7821 | 0.1790          | 0.8305    | 0.8629 | 0.8464 | 0.9559   |
+
+
+### Framework versions
+
+- Transformers 4.28.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.12.0
+- Tokenizers 0.13.3