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ZhiguangHan
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mt5-small-task3-dataset3

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@@ -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 [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0516
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  - Rouge1: 0.0
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  - Rouge2: 0.0
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  - Rougel: 0.0
@@ -46,19 +46,20 @@ 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: 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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- | 2.0315 | 1.0 | 500 | 0.0727 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | 0.1434 | 2.0 | 1000 | 0.0660 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | 0.0975 | 3.0 | 1500 | 0.0613 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | 0.0822 | 4.0 | 2000 | 0.0554 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | 0.0806 | 5.0 | 2500 | 0.0543 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | 0.0745 | 6.0 | 3000 | 0.0535 | 0.0 | 0.0 | 0.0 | 0.0 |
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- | 0.0713 | 7.0 | 3500 | 0.0516 | 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 [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0802
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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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  - 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: 8
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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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+ | 4.8701 | 1.0 | 500 | 0.1153 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.1204 | 2.0 | 1000 | 0.1054 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.1014 | 3.0 | 1500 | 0.0837 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.0898 | 4.0 | 2000 | 0.0861 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.083 | 5.0 | 2500 | 0.0931 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.0784 | 6.0 | 3000 | 0.0810 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.0763 | 7.0 | 3500 | 0.0845 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.0743 | 8.0 | 4000 | 0.0802 | 0.0 | 0.0 | 0.0 | 0.0 |
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  ### Framework versions