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ViNormT5

Text2Text Generation
Transformers
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Safetensors
t5
Generated from Trainer
text-generation-inference
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  1. README.md +11 -10
  2. logs/events.out.tfevents.1727533392.f41cea15f6e1.2276.3 +2 -2
  3. model.safetensors +1 -1
README.md CHANGED
@@ -19,12 +19,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [VietAI/vit5-base](https://huggingface.co/VietAI/vit5-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2178
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- - Bleu Score: 78.7261
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- - Precision: 54.5998
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- - Recall: 54.5998
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- - Gen Len: 12.7826
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- - Err: 54.5998
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  ## Model description
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@@ -49,15 +49,16 @@ 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: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Bleu Score | Precision | Recall | Gen Len | Err |
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  |:-------------:|:-----:|:----:|:---------------:|:----------:|:---------:|:-------:|:-------:|:-------:|
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- | 0.4635 | 1.0 | 419 | 0.2255 | 77.2678 | 49.5818 | 49.5818 | 12.7969 | 49.5818 |
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- | 0.166 | 2.0 | 838 | 0.2026 | 78.2851 | 53.1661 | 53.1661 | 12.8041 | 53.1661 |
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- | 0.0752 | 3.0 | 1257 | 0.2178 | 78.7261 | 54.5998 | 54.5998 | 12.7826 | 54.5998 |
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [VietAI/vit5-base](https://huggingface.co/VietAI/vit5-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2324
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+ - Bleu Score: 79.5557
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+ - Precision: 56.9892
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+ - Recall: 56.9892
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+ - Gen Len: 12.7969
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+ - Err: 56.9892
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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: 4
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Bleu Score | Precision | Recall | Gen Len | Err |
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  |:-------------:|:-----:|:----:|:---------------:|:----------:|:---------:|:-------:|:-------:|:-------:|
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+ | 0.4672 | 1.0 | 419 | 0.2390 | 76.7871 | 49.7013 | 49.7013 | 12.8292 | 49.7013 |
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+ | 0.1742 | 2.0 | 838 | 0.2173 | 77.9698 | 54.0024 | 54.0024 | 12.8076 | 54.0024 |
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+ | 0.0814 | 3.0 | 1257 | 0.2010 | 79.204 | 56.6308 | 56.6308 | 12.7754 | 56.6308 |
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+ | 0.0382 | 4.0 | 1676 | 0.2324 | 79.5557 | 56.9892 | 56.9892 | 12.7969 | 56.9892 |
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  ### Framework versions
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