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End of training

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README.md CHANGED
@@ -17,7 +17,7 @@ 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: 1.6515
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  - Rouge1: 0.0
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  - Rouge2: 0.0
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  - Rougel: 0.0
@@ -49,48 +49,23 @@ The following hyperparameters were used during training:
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  - total_train_batch_size: 10
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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: 35
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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 | Gen Len |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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- | No log | 1.0 | 6 | 16.2560 | 0.0609 | 0.0143 | 0.0529 | 0.0528 | 19.0 |
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- | No log | 2.0 | 12 | 14.2686 | 0.0602 | 0.0128 | 0.0516 | 0.0516 | 19.0 |
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- | No log | 3.0 | 18 | 12.3755 | 0.0639 | 0.0134 | 0.0548 | 0.0548 | 19.0 |
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- | No log | 4.0 | 24 | 10.4025 | 0.067 | 0.0115 | 0.0547 | 0.0547 | 19.0 |
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- | No log | 5.0 | 30 | 8.6351 | 0.0682 | 0.0131 | 0.0551 | 0.0553 | 19.0 |
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- | No log | 6.0 | 36 | 7.3856 | 0.0682 | 0.0131 | 0.0551 | 0.0553 | 19.0 |
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- | No log | 7.0 | 42 | 6.3727 | 0.0687 | 0.0131 | 0.0557 | 0.0557 | 19.0 |
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- | No log | 8.0 | 48 | 5.4948 | 0.0683 | 0.0136 | 0.0557 | 0.0558 | 19.0 |
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- | No log | 9.0 | 54 | 4.6428 | 0.0683 | 0.0132 | 0.0554 | 0.0553 | 19.0 |
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- | No log | 10.0 | 60 | 3.8533 | 0.0683 | 0.0132 | 0.0554 | 0.0553 | 19.0 |
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- | No log | 11.0 | 66 | 3.1973 | 0.0524 | 0.0105 | 0.0412 | 0.0419 | 15.2 |
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- | No log | 12.0 | 72 | 2.7078 | 0.0419 | 0.0074 | 0.0336 | 0.034 | 11.4 |
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- | No log | 13.0 | 78 | 2.3688 | 0.0266 | 0.0052 | 0.0234 | 0.0237 | 7.6 |
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- | No log | 14.0 | 84 | 2.1534 | 0.007 | 0.002 | 0.0065 | 0.0065 | 1.9 |
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- | No log | 15.0 | 90 | 2.0260 | 0.0052 | 0.0015 | 0.0052 | 0.0052 | 1.9 |
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- | No log | 16.0 | 96 | 1.9478 | 0.0024 | 0.001 | 0.0024 | 0.0024 | 0.95 |
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- | No log | 17.0 | 102 | 1.8972 | 0.0024 | 0.001 | 0.0024 | 0.0024 | 0.95 |
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- | No log | 18.0 | 108 | 1.8585 | 0.0024 | 0.001 | 0.0024 | 0.0024 | 0.95 |
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- | No log | 19.0 | 114 | 1.8262 | 0.0024 | 0.001 | 0.0024 | 0.0024 | 0.95 |
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- | No log | 20.0 | 120 | 1.7977 | 0.0024 | 0.001 | 0.0024 | 0.0024 | 0.95 |
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- | No log | 21.0 | 126 | 1.7731 | 0.0038 | 0.0014 | 0.0033 | 0.0033 | 0.95 |
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- | No log | 22.0 | 132 | 1.7483 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 23.0 | 138 | 1.7304 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 24.0 | 144 | 1.7155 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 25.0 | 150 | 1.7025 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 26.0 | 156 | 1.6914 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 27.0 | 162 | 1.6825 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 28.0 | 168 | 1.6755 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 29.0 | 174 | 1.6691 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 30.0 | 180 | 1.6640 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 31.0 | 186 | 1.6599 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 32.0 | 192 | 1.6566 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 33.0 | 198 | 1.6541 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 34.0 | 204 | 1.6524 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | No log | 35.0 | 210 | 1.6515 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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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: 2.5079
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  - Rouge1: 0.0
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  - Rouge2: 0.0
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  - Rougel: 0.0
 
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  - total_train_batch_size: 10
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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 | Gen Len |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
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+ | No log | 1.0 | 6 | 2.6066 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 2.0 | 12 | 2.5867 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 3.0 | 18 | 2.5701 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 4.0 | 24 | 2.5554 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 5.0 | 30 | 2.5405 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 6.0 | 36 | 2.5292 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 7.0 | 42 | 2.5207 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 8.0 | 48 | 2.5145 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 9.0 | 54 | 2.5102 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | No log | 10.0 | 60 | 2.5079 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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