update model card README.md

README.md

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+---
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_trainer
+datasets:
+- azaheadhealth
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: azahead-bert-v1.0
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: azaheadhealth
+      type: azaheadhealth
+      config: small
+      split: test
+      args: small
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.7916666666666666
+    - name: F1
+      type: f1
+      value: 0.6666666666666666
+    - name: Precision
+      type: precision
+      value: 0.625
+    - name: Recall
+      type: recall
+      value: 0.7142857142857143
+---
+
+<!-- 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. -->
+
+# azahead-bert-v1.0
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the azaheadhealth dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5108
+- Accuracy: 0.7917
+- F1: 0.6667
+- Precision: 0.625
+- Recall: 0.7143
+
+## 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 | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.6157        | 1.0   | 20   | 0.5087          | 0.7083   | 0.0    | 0.0       | 0.0    |
+| 0.4057        | 2.0   | 40   | 0.5892          | 0.7083   | 0.2222 | 0.5       | 0.1429 |
+| 0.2788        | 3.0   | 60   | 0.4834          | 0.7917   | 0.4444 | 1.0       | 0.2857 |
+| 0.1726        | 4.0   | 80   | 0.5108          | 0.7917   | 0.6667 | 0.625     | 0.7143 |
+| 0.1271        | 5.0   | 100  | 0.6210          | 0.7917   | 0.6154 | 0.6667    | 0.5714 |
+| 0.1045        | 6.0   | 120  | 0.6850          | 0.7917   | 0.6154 | 0.6667    | 0.5714 |
+| 0.0108        | 7.0   | 140  | 0.7771          | 0.75     | 0.5714 | 0.5714    | 0.5714 |
+| 0.0248        | 8.0   | 160  | 0.8454          | 0.7917   | 0.6154 | 0.6667    | 0.5714 |
+| 0.0152        | 9.0   | 180  | 0.8667          | 0.7917   | 0.6154 | 0.6667    | 0.5714 |
+| 0.0064        | 10.0  | 200  | 0.8776          | 0.75     | 0.5714 | 0.5714    | 0.5714 |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.2.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.13.2