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ViNormT5

Text2Text Generation
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Safetensors
t5
Generated from Trainer
text-generation-inference
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End of training

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  1. README.md +11 -10
  2. logs/events.out.tfevents.1727539836.d84cb60c1073.5349.1 +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: 0.2379
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- - Bleu Score: 79.1915
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- - Precision: 56.3919
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- - Recall: 56.3919
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- - Gen Len: 12.7861
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- - Err: 56.3919
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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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- | 0.537 | 1.0 | 838 | 0.2957 | 75.5178 | 47.3118 | 47.3118 | 12.8029 | 47.3118 |
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- | 0.2145 | 2.0 | 1676 | 0.2338 | 78.5376 | 54.5998 | 54.5998 | 12.8005 | 54.5998 |
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- | 0.0834 | 3.0 | 2514 | 0.2379 | 79.1915 | 56.3919 | 56.3919 | 12.7861 | 56.3919 |
 
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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: 0.2580
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+ - Bleu Score: 79.3456
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+ - Precision: 57.4671
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+ - Recall: 57.4671
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+ - Gen Len: 12.7694
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+ - Err: 57.4671
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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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+ | 0.5544 | 1.0 | 838 | 0.2951 | 75.8053 | 45.9976 | 45.9976 | 12.6918 | 45.9976 |
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+ | 0.2306 | 2.0 | 1676 | 0.2519 | 77.9908 | 51.9713 | 51.9713 | 12.7515 | 51.9713 |
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+ | 0.1091 | 3.0 | 2514 | 0.2437 | 78.935 | 54.9582 | 54.9582 | 12.7778 | 54.9582 |
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+ | 0.0435 | 4.0 | 3352 | 0.2580 | 79.3456 | 57.4671 | 57.4671 | 12.7694 | 57.4671 |
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  ### Framework versions
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