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--- |
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license: apache-2.0 |
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base_model: google/flan-t5-base |
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tags: |
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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: AI_Chaperone |
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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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# AI_Chaperone |
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This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4868 |
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- Rouge1: 0.1544 |
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- Rouge2: 0.0388 |
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- Rougel: 0.1494 |
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- Rougelsum: 0.1493 |
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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: 0.0003 |
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- train_batch_size: 8 |
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- eval_batch_size: 4 |
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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: 10 |
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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 | 375 | 0.8740 | 0.1454 | 0.0294 | 0.1416 | 0.1420 | |
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| 1.2229 | 2.0 | 750 | 0.8700 | 0.1572 | 0.0445 | 0.1526 | 0.1533 | |
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| 0.6201 | 3.0 | 1125 | 0.9088 | 0.1639 | 0.0461 | 0.1616 | 0.1606 | |
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| 0.4623 | 4.0 | 1500 | 0.9650 | 0.1581 | 0.0457 | 0.1533 | 0.1537 | |
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| 0.4623 | 5.0 | 1875 | 1.0441 | 0.1487 | 0.0332 | 0.1436 | 0.1437 | |
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| 0.3399 | 6.0 | 2250 | 1.1880 | 0.1581 | 0.0436 | 0.1528 | 0.1533 | |
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| 0.2692 | 7.0 | 2625 | 1.2633 | 0.1582 | 0.0423 | 0.1539 | 0.1547 | |
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| 0.2233 | 8.0 | 3000 | 1.3449 | 0.1624 | 0.0409 | 0.1590 | 0.1593 | |
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| 0.2233 | 9.0 | 3375 | 1.4225 | 0.1555 | 0.0401 | 0.1513 | 0.1507 | |
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| 0.183 | 10.0 | 3750 | 1.4868 | 0.1544 | 0.0388 | 0.1494 | 0.1493 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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