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update model card README.md
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README.md
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---
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license: apache-2.0
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base_model: allenai/longformer-base-4096
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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: azahead-longformer-v1.0
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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: small
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split: test
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args: small
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.7916666666666666
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- name: F1
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type: f1
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value: 0.6666666666666666
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- name: Precision
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type: precision
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value: 0.625
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- name: Recall
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type: recall
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value: 0.7142857142857143
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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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# azahead-longformer-v1.0
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This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co/allenai/longformer-base-4096) on the azaheadhealth dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6326
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- Accuracy: 0.7917
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- F1: 0.6667
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- Precision: 0.625
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- Recall: 0.7143
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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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: 2
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 8
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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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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| 0.6853 | 1.0 | 20 | 0.6326 | 0.7917 | 0.6667 | 0.625 | 0.7143 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.2.1+cu121
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- Datasets 2.16.1
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- Tokenizers 0.13.2
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