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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-Emot-EmotNn
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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-Emot-EmotNn
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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: 0.3559
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- Rouge1: 0.8119
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- Rouge2: 0.2070
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- Rougel: 0.8102
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- Rougelsum: 0.8115
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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: 32
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- eval_batch_size: 32
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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 | 24 | 0.5128 | 0.5154 | 0.0562 | 0.5072 | 0.5086 |
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| No log | 2.0 | 48 | 0.3782 | 0.7132 | 0.0145 | 0.7127 | 0.7159 |
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| No log | 3.0 | 72 | 0.3387 | 0.7872 | 0.1712 | 0.7745 | 0.7756 |
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| No log | 4.0 | 96 | 0.3221 | 0.7804 | 0.1598 | 0.7754 | 0.7777 |
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| No log | 5.0 | 120 | 0.3669 | 0.7453 | 0.1330 | 0.7403 | 0.7414 |
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| No log | 6.0 | 144 | 0.3559 | 0.8119 | 0.2070 | 0.8102 | 0.8115 |
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| No log | 7.0 | 168 | 0.3559 | 0.8047 | 0.1895 | 0.8036 | 0.8047 |
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| No log | 8.0 | 192 | 0.3808 | 0.7967 | 0.1925 | 0.7934 | 0.7949 |
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| No log | 9.0 | 216 | 0.3899 | 0.8047 | 0.2127 | 0.8030 | 0.8040 |
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| No log | 10.0 | 240 | 0.3991 | 0.8096 | 0.2247 | 0.8068 | 0.8074 |
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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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