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--- |
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license: apache-2.0 |
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base_model: google/flan-t5-small |
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tags: |
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- text2textgeneration |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: flan-t5-small-finetune-medicine-v3 |
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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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# flan-t5-small-finetune-medicine-v3 |
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This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.8757 |
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- Rouge1: 15.991 |
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- Rouge2: 5.2469 |
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- Rougel: 14.6278 |
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- Rougelsum: 14.7076 |
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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: 5.6e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:| |
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| No log | 1.0 | 5 | 2.9996 | 12.4808 | 4.9536 | 12.3712 | 12.2123 | |
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| No log | 2.0 | 10 | 2.9550 | 13.6471 | 4.9536 | 13.5051 | 13.5488 | |
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| No log | 3.0 | 15 | 2.9224 | 13.8077 | 5.117 | 13.7274 | 13.753 | |
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| No log | 4.0 | 20 | 2.9050 | 13.7861 | 5.117 | 13.6982 | 13.7001 | |
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| No log | 5.0 | 25 | 2.8920 | 14.668 | 5.117 | 14.4497 | 14.4115 | |
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| No log | 6.0 | 30 | 2.8820 | 14.9451 | 5.2469 | 14.5797 | 14.6308 | |
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| No log | 7.0 | 35 | 2.8770 | 15.991 | 5.2469 | 14.6278 | 14.7076 | |
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| No log | 8.0 | 40 | 2.8757 | 15.991 | 5.2469 | 14.6278 | 14.7076 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.1 |
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- Tokenizers 0.13.3 |
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