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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: MedAware |
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results: [] |
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datasets: |
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- keivalya/MedQuad-MedicalQnADataset |
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language: |
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- en |
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pipeline_tag: text-generation |
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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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# MedAware |
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This model is a fine-tuned version of [euclaise/falcon_1b_stage2](https://huggingface.co/euclaise/falcon_1b_stage2) on MedQuAD: Medical Question Answering Dataset. |
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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: 0.0002 |
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- train_batch_size: 4 |
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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: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.05 |
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- num_epochs: 1 |
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### Training results |
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Training steps: 1025/1025; time- 2:45:21 |
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| Steps | Training_loss | |
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|-------|---------------| |
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| 500 | 1.273800 | |
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| 1000 | 1.133000 | |
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TrainOutput(global_step=1025, training_loss=1.1994486794820647, metrics={'train_runtime': 9932.0844, 'train_samples_per_second': 1.652, 'train_steps_per_second': 0.103, 'total_flos': 3.2484758758785024e+16, 'train_loss': 1.1994486794820647, 'epoch': 1.0}) |
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### Framework versions |
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- Transformers 4.30.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
