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: bert-azahead-v0.1
+  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: 0.75
+    - name: F1
+      type: f1
+      value: 0.4
+    - name: Precision
+      type: precision
+      value: 0.6666666666666666
+    - name: Recall
+      type: recall
+      value: 0.2857142857142857
+---
+
+<!-- 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-azahead-v0.1
+
+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: 0.4710
+- Accuracy: 0.75
+- F1: 0.4
+- Precision: 0.6667
+- Recall: 0.2857
+
+## 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: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 4
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.6325        | 0.5   | 20   | 0.5001          | 0.7917   | 0.7059 | 0.6       | 0.8571 |
+| 0.5346        | 1.0   | 40   | 0.4710          | 0.75     | 0.4    | 0.6667    | 0.2857 |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.2.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.13.2