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: medlid-identify
+  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. -->
+
+# medlid-identify
+
+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: 0.2110
+- Precision: 0.2629
+- Recall: 0.2839
+- F1: 0.2730
+- Accuracy: 0.9138
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 81
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 35   | 0.2354          | 0.0346    | 0.0224 | 0.0272 | 0.9101   |
+| No log        | 2.0   | 70   | 0.2147          | 0.2044    | 0.2019 | 0.2031 | 0.9127   |
+| No log        | 3.0   | 105  | 0.2185          | 0.2336    | 0.3033 | 0.2639 | 0.9077   |
+| No log        | 4.0   | 140  | 0.2110          | 0.2629    | 0.2839 | 0.2730 | 0.9138   |
+
+
+### Framework versions
+
+- Transformers 4.30.2
+- Pytorch 1.11.0
+- Datasets 2.13.1
+- Tokenizers 0.13.3