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mt5-small-task3-dataset1

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  1. README.md +24 -18
  2. model.safetensors +1 -1
README.md CHANGED
@@ -17,8 +17,11 @@ 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 the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.3592
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- - Accuracy: 0.14
 
 
 
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  ## Model description
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@@ -43,29 +46,32 @@ 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: 12
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 1.6139 | 1.0 | 250 | 1.3916 | 0.102 |
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- | 1.5289 | 2.0 | 500 | 1.4550 | 0.108 |
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- | 1.4823 | 3.0 | 750 | 1.3630 | 0.132 |
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- | 1.4372 | 4.0 | 1000 | 1.3930 | 0.116 |
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- | 1.4563 | 5.0 | 1250 | 1.3857 | 0.124 |
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- | 1.4347 | 6.0 | 1500 | 1.3708 | 0.124 |
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- | 1.4303 | 7.0 | 1750 | 1.3856 | 0.136 |
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- | 1.4072 | 8.0 | 2000 | 1.3595 | 0.136 |
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- | 1.4045 | 9.0 | 2250 | 1.3677 | 0.13 |
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- | 1.3861 | 10.0 | 2500 | 1.3511 | 0.13 |
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- | 1.376 | 11.0 | 2750 | 1.3543 | 0.136 |
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- | 1.3699 | 12.0 | 3000 | 1.3592 | 0.14 |
 
 
 
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  ### Framework versions
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  - Transformers 4.35.2
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- - Pytorch 2.1.0+cu118
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  - Datasets 2.15.0
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  - Tokenizers 0.15.0
 
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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: 1.3494
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+ - Accuracy: 0.156
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+ - Mse: 1.4726
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+ - Log-distance: 0.6559
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+ - S Score: 0.5092
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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: 15
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Mse | Log-distance | S Score |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------------:|:-------:|
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+ | 12.3227 | 1.0 | 250 | 3.0911 | 0.126 | 1.6773 | 0.5862 | 0.5608 |
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+ | 3.0171 | 2.0 | 500 | 1.8496 | 0.126 | 1.6805 | 0.5886 | 0.5608 |
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+ | 2.1379 | 3.0 | 750 | 1.4488 | 0.126 | 1.6773 | 0.5862 | 0.5608 |
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+ | 1.7896 | 4.0 | 1000 | 1.4309 | 0.126 | 1.6773 | 0.5862 | 0.5608 |
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+ | 1.6843 | 5.0 | 1250 | 1.3863 | 0.136 | 1.5477 | 0.5660 | 0.5764 |
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+ | 1.6196 | 6.0 | 1500 | 1.3676 | 0.142 | 1.4865 | 0.6943 | 0.4700 |
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+ | 1.5812 | 7.0 | 1750 | 1.3518 | 0.14 | 1.4748 | 0.6894 | 0.4728 |
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+ | 1.5336 | 8.0 | 2000 | 1.3538 | 0.148 | 1.6125 | 0.7828 | 0.4220 |
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+ | 1.5106 | 9.0 | 2250 | 1.3468 | 0.172 | 1.4330 | 0.6204 | 0.5484 |
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+ | 1.486 | 10.0 | 2500 | 1.3519 | 0.16 | 1.4487 | 0.6414 | 0.5268 |
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+ | 1.4524 | 11.0 | 2750 | 1.3465 | 0.156 | 1.3796 | 0.5703 | 0.5720 |
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+ | 1.4614 | 12.0 | 3000 | 1.3494 | 0.162 | 1.4250 | 0.6270 | 0.5316 |
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+ | 1.4525 | 13.0 | 3250 | 1.3589 | 0.146 | 1.4602 | 0.6592 | 0.5068 |
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+ | 1.4379 | 14.0 | 3500 | 1.3505 | 0.154 | 1.4722 | 0.6524 | 0.5128 |
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+ | 1.4397 | 15.0 | 3750 | 1.3494 | 0.156 | 1.4726 | 0.6559 | 0.5092 |
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  ### Framework versions
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  - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu121
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  - Datasets 2.15.0
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  - Tokenizers 0.15.0
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