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mt5-small-finetuned-b8-10-local

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mt5
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End of training

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  1. README.md +18 -12
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -15,11 +15,11 @@ 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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.6132
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- - Rouge-1: 4.484
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- - Rouge-2: 0.423
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- - Rouge-l: 4.328
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- - Gen Len: 7.4243
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  ## Model description
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@@ -46,16 +46,22 @@ The following hyperparameters were used during training:
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  - total_train_batch_size: 16
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  - optimizer: Adafactor
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  - lr_scheduler_type: linear
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- - num_epochs: 4
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len |
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- |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:-------:|
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- | 9.3715 | 1.0 | 1356 | 7.0740 | 5.8475 | 0.7165 | 5.4416 | 13.9752 |
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- | 4.1207 | 2.0 | 2713 | 3.7971 | 3.4679 | 0.1967 | 3.3715 | 6.4055 |
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- | 3.1187 | 3.0 | 4070 | 2.8037 | 3.9821 | 0.3095 | 3.8062 | 6.1261 |
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- | 3.0094 | 4.0 | 5424 | 2.6132 | 4.484 | 0.423 | 4.328 | 7.4243 |
 
 
 
 
 
 
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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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 3.5178
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+ - Rouge-1: 22.6249
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+ - Rouge-2: 7.9752
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+ - Rouge-l: 20.3546
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+ - Gen Len: 17.0843
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  ## Model description
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  - total_train_batch_size: 16
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  - optimizer: Adafactor
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  - lr_scheduler_type: linear
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+ - num_epochs: 10
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  ### Training results
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+ | Training Loss | Epoch | Step | Gen Len | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l |
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+ |:-------------:|:-----:|:-----:|:-------:|:---------------:|:-------:|:-------:|:-------:|
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+ | 5.111 | 1.0 | 1356 | 12.3837 | 4.0081 | 18.105 | 6.0904 | 16.8637 |
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+ | 4.5548 | 2.0 | 2712 | 3.8803 | 19.8119 | 6.9894 | 18.2397 | 14.1547 |
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+ | 4.3667 | 3.0 | 4069 | 3.7301 | 21.0826 | 7.3597 | 19.1813 | 16.1043 |
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+ | 4.1807 | 4.0 | 5426 | 3.6560 | 21.6212 | 7.5877 | 19.5831 | 16.7592 |
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+ | 4.1524 | 5.0 | 6783 | 3.5911 | 22.0587 | 7.6506 | 19.9304 | 16.7987 |
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+ | 4.1061 | 6.0 | 8140 | 3.5603 | 22.1661 | 7.7772 | 19.9915 | 16.8959 |
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+ | 4.0028 | 7.0 | 9497 | 3.5431 | 22.6005 | 7.9698 | 20.3279 | 16.9174 |
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+ | 3.9558 | 8.0 | 10854 | 3.5305 | 22.6074 | 7.9613 | 20.3267 | 17.0914 |
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+ | 3.9647 | 9.0 | 12211 | 3.5207 | 22.5858 | 7.947 | 20.2764 | 17.0981 |
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+ | 4.0044 | 9.99 | 13560 | 3.5178 | 22.6249 | 7.9752 | 20.3546 | 17.0843 |
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  ### Framework versions
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