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basso4
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basso4_eng_to_vie_model

Text2Text Generation
Transformers
PyTorch
t5
generated_from_trainer
Eval Results
Inference Endpoints
text-generation-inference
Model card Files Community
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  1. README.md +16 -10
  2. pytorch_model.bin +1 -1
README.md CHANGED
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  ---
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- license: apache-2.0
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- base_model: t5-small
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  tags:
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  - generated_from_trainer
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  datasets:
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  metrics:
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  - name: Bleu
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  type: bleu
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- value: 0.2843
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -30,11 +28,11 @@ should probably proofread and complete it, then remove this comment. -->
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  # basso4_eng_to_vie_model
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- This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the mt_eng_vietnamese dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.4992
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- - Bleu: 0.2843
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- - Gen Len: 18.7733
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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: 2
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
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  |:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|
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- | 1.7028 | 1.0 | 6666 | 1.5587 | 0.1992 | 18.7357 |
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- | 1.6335 | 2.0 | 13332 | 1.4992 | 0.2843 | 18.7733 |
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  ---
 
 
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  tags:
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  - generated_from_trainer
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  datasets:
 
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  metrics:
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  - name: Bleu
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  type: bleu
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+ value: 1.3777
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  # basso4_eng_to_vie_model
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+ This model was trained from scratch on the mt_eng_vietnamese dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.9999
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+ - Bleu: 1.3777
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+ - Gen Len: 18.7953
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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: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
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  |:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|
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+ | 1.3485 | 1.0 | 6666 | 1.2151 | 0.9294 | 18.7893 |
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+ | 1.2969 | 2.0 | 13332 | 1.1510 | 1.0593 | 18.7881 |
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+ | 1.2426 | 3.0 | 19998 | 1.1053 | 1.1598 | 18.7873 |
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+ | 1.2067 | 4.0 | 26664 | 1.0713 | 1.2393 | 18.789 |
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+ | 1.1809 | 5.0 | 33330 | 1.0469 | 1.2853 | 18.7894 |
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+ | 1.1575 | 6.0 | 39996 | 1.0288 | 1.3227 | 18.7899 |
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+ | 1.1407 | 7.0 | 46662 | 1.0154 | 1.3405 | 18.7937 |
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+ | 1.1295 | 8.0 | 53328 | 1.0071 | 1.3657 | 18.7943 |
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+ | 1.1241 | 9.0 | 59994 | 1.0014 | 1.3753 | 18.7953 |
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+ | 1.1209 | 10.0 | 66660 | 0.9999 | 1.3777 | 18.7953 |
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  ### Framework versions
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