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update model card README.md

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+ ---
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+ license: apache-2.0
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+ base_model: bert-base-uncased
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - azaheadhealth
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+ metrics:
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+ - accuracy
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+ - f1
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+ - precision
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+ - recall
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+ model-index:
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+ - name: microtest-2.0
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+ results:
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+ - task:
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+ name: Text Classification
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+ type: text-classification
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+ dataset:
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+ name: azaheadhealth
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+ type: azaheadhealth
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+ config: micro
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+ split: test
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+ args: micro
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.75
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+ - name: F1
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+ type: f1
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+ value: 0.8
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+ - name: Precision
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+ type: precision
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+ value: 0.6666666666666666
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+ - name: Recall
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+ type: recall
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+ value: 1.0
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # microtest-2.0
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+
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+ This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the azaheadhealth dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3672
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+ - Accuracy: 0.75
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+ - F1: 0.8
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+ - Precision: 0.6667
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+ - Recall: 1.0
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 1
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+ - eval_batch_size: 1
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 2
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 1
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---:|:---------:|:------:|
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+ | 0.8113 | 0.5 | 1 | 0.4486 | 0.75 | 0.8 | 0.6667 | 1.0 |
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+ | 0.7227 | 1.0 | 2 | 0.3672 | 0.75 | 0.8 | 0.6667 | 1.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.31.0
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+ - Pytorch 2.2.0+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.13.2