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update model card README.md

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@@ -14,15 +14,10 @@ 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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - eval_loss: 1.8403
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- - eval_rouge2_precision: 0.298
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- - eval_rouge2_recall: 0.1943
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- - eval_rouge2_fmeasure: 0.2198
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- - eval_runtime: 4.1041
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- - eval_samples_per_second: 43.372
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- - eval_steps_per_second: 2.924
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- - epoch: 5.0
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- - step: 500
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  ## Model description
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@@ -47,12 +42,28 @@ 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: 15
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  - mixed_precision_training: Native AMP
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  ### Framework versions
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- - Transformers 4.12.2
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  - Pytorch 1.9.0+cu111
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- - Datasets 1.14.0
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  - Tokenizers 0.10.3
 
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  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.6131
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+ - Rouge2 Precision: 0.3
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+ - Rouge2 Recall: 0.2152
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+ - Rouge2 Fmeasure: 0.2379
 
 
 
 
 
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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: 10
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  - mixed_precision_training: Native AMP
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
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+ |:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
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+ | 2.1335 | 1.0 | 563 | 1.7632 | 0.2716 | 0.1936 | 0.2135 |
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+ | 1.9373 | 2.0 | 1126 | 1.7037 | 0.2839 | 0.2068 | 0.2265 |
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+ | 1.8827 | 3.0 | 1689 | 1.6723 | 0.2901 | 0.2118 | 0.2316 |
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+ | 1.8257 | 4.0 | 2252 | 1.6503 | 0.2938 | 0.2115 | 0.2332 |
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+ | 1.8152 | 5.0 | 2815 | 1.6386 | 0.2962 | 0.2139 | 0.2357 |
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+ | 1.7939 | 6.0 | 3378 | 1.6284 | 0.2976 | 0.212 | 0.2354 |
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+ | 1.7845 | 7.0 | 3941 | 1.6211 | 0.2991 | 0.2155 | 0.2383 |
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+ | 1.7468 | 8.0 | 4504 | 1.6167 | 0.2994 | 0.217 | 0.239 |
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+ | 1.7464 | 9.0 | 5067 | 1.6137 | 0.3007 | 0.2154 | 0.2382 |
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+ | 1.744 | 10.0 | 5630 | 1.6131 | 0.3 | 0.2152 | 0.2379 |
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  ### Framework versions
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+ - Transformers 4.12.3
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  - Pytorch 1.9.0+cu111
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+ - Datasets 1.15.1
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  - Tokenizers 0.10.3