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update model card README.md

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@@ -17,11 +17,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.9807
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- - Rouge1: 14.227
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- - Rouge2: 4.3001
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- - Rougel: 10.7052
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- - Rougelsum: 12.5784
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  ## Model description
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@@ -46,15 +46,19 @@ The following hyperparameters were used during training:
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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: 3
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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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- | 3.489 | 1.0 | 250 | 3.0402 | 14.1245 | 4.3869 | 10.6829 | 12.78 |
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- | 3.2405 | 2.0 | 500 | 2.9928 | 14.0471 | 4.1959 | 10.6048 | 12.4612 |
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- | 3.1865 | 3.0 | 750 | 2.9807 | 14.227 | 4.3001 | 10.7052 | 12.5784 |
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.8049
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+ - Rouge1: 15.1241
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+ - Rouge2: 4.9514
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+ - Rougel: 11.5019
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+ - Rougelsum: 13.3079
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  ## Model description
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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: 7
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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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+ | 3.2411 | 1.0 | 1250 | 2.8772 | 14.6774 | 4.7697 | 11.335 | 13.0082 |
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+ | 3.079 | 2.0 | 2500 | 2.8438 | 14.9558 | 4.8748 | 11.4023 | 13.2198 |
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+ | 3.0257 | 3.0 | 3750 | 2.8240 | 15.133 | 4.9814 | 11.572 | 13.3607 |
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+ | 2.9903 | 4.0 | 5000 | 2.8153 | 15.1339 | 4.9123 | 11.5038 | 13.3464 |
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+ | 2.9659 | 5.0 | 6250 | 2.8085 | 15.1134 | 5.0057 | 11.5478 | 13.3483 |
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+ | 2.9461 | 6.0 | 7500 | 2.8066 | 15.154 | 4.9641 | 11.5276 | 13.3523 |
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+ | 2.936 | 7.0 | 8750 | 2.8049 | 15.1241 | 4.9514 | 11.5019 | 13.3079 |
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  ### Framework versions