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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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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: t5-base-DreamBank-Generation-NER-Char
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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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# t5-base-DreamBank-Generation-NER-Char
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This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4674
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- Rouge1: 0.7853
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- Rouge2: 0.6927
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- Rougel: 0.7564
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- Rougelsum: 0.7565
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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: 16
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- eval_batch_size: 16
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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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- mixed_precision_training: Native AMP
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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 | 93 | 0.6486 | 0.5936 | 0.4495 | 0.5705 | 0.5701 |
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| No log | 2.0 | 186 | 0.5363 | 0.7196 | 0.6020 | 0.6990 | 0.6983 |
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| No log | 3.0 | 279 | 0.4391 | 0.7568 | 0.6459 | 0.7235 | 0.7244 |
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| No log | 4.0 | 372 | 0.4223 | 0.7751 | 0.6748 | 0.7473 | 0.7477 |
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| No log | 5.0 | 465 | 0.4266 | 0.7789 | 0.6746 | 0.7512 | 0.7522 |
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| 0.6336 | 6.0 | 558 | 0.4296 | 0.7810 | 0.6790 | 0.7537 | 0.7539 |
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| 0.6336 | 7.0 | 651 | 0.4400 | 0.7798 | 0.6808 | 0.7537 | 0.7543 |
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| 0.6336 | 8.0 | 744 | 0.4497 | 0.7749 | 0.6821 | 0.7471 | 0.7481 |
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| 0.6336 | 9.0 | 837 | 0.4661 | 0.7828 | 0.6910 | 0.7554 | 0.7563 |
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| 0.6336 | 10.0 | 930 | 0.4674 | 0.7853 | 0.6927 | 0.7564 | 0.7565 |
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### Framework versions
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- Transformers 4.25.1
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- Pytorch 1.12.1
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- Datasets 2.5.1
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- Tokenizers 0.12.1
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