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--- |
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library_name: transformers |
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base_model: yikuan8/Clinical-Longformer |
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tags: |
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- generated_from_trainer |
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datasets: |
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- squad_v2 |
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model-index: |
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- name: clinical_longformer_squadv2_maxlen320 |
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results: [] |
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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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# clinical_longformer_squadv2_maxlen320 |
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This model is a fine-tuned version of [yikuan8/Clinical-Longformer](https://huggingface.co/yikuan8/Clinical-Longformer) on the squad_v2 dataset using a max_seq_length of 320. |
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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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Tuning script used: |
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```python |
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set BASE_MODEL=yikuan8/Clinical-Longformer |
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set OUTPUT_DIR=U:\Documents... |
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python run_qa.py ^ |
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--model_name_or_path %BASE_MODEL% ^ |
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--dataset_name squad_v2 ^ |
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--do_train ^ |
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--do_eval ^ |
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--version_2_with_negative ^ |
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--per_device_train_batch_size 4 ^ |
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--per_device_eval_batch_size 4 ^ |
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--gradient_accumulation_steps 4 ^ |
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--learning_rate 2e-5 ^ |
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--num_train_epochs 3 ^ |
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--max_seq_length 320 ^ |
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--doc_stride 128 ^ |
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--weight_decay 0.01 ^ |
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--fp16 ^ |
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--output_dir %OUTPUT_DIR% ^ |
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--overwrite_output_dir |
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``` |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 3.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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### Framework versions |
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- Transformers 4.48.0.dev0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 3.0.1 |
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- Tokenizers 0.21.0 |
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