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sc20fg
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base_model_base_tokenizer

Text2Text Generation
Transformers
Safetensors
t5
Generated from Trainer
Eval Results
text-generation-inference
Inference Endpoints
Model card Files Community
sc20fg commited on
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End of training

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Files changed (3) hide show
  1. README.md +8 -8
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Bleu
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  type: bleu
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- value: 0.07436694391946623
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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
@@ -34,10 +34,10 @@ This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base)
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  It achieves the following results on the evaluation set:
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  - Loss: 2.1017
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  - Bleu: 0.0744
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- - Precisions: [0.3738987404904811, 0.14063074178287074, 0.0757991255723879, 0.045524517425472845]
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- - Brevity Penalty: 0.6408
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  - Length Ratio: 0.6920
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- - Translation Length: 585466
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  - Reference Length: 846059
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  ## Model description
@@ -85,10 +85,10 @@ The following hyperparameters were used during training:
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  | 1.9811 | 14.0 | 360668 | 0.0718 | 0.6325 | 0.6858 | 2.1096 | [0.37342310979981247, 0.13867710694415825, 0.0736328303569596, 0.043440268414579084] | 846059 | 580256 |
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  | 1.9745 | 15.0 | 386430 | 0.0741 | 0.6592 | 0.7059 | 2.1060 | [0.36869699176985743, 0.13724429728380805, 0.07301699268383118, 0.04318353520566863] | 846059 | 597195 |
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  | 1.939 | 16.0 | 412192 | 0.0706 | 0.6166 | 0.6740 | 2.1063 | [0.37537898781101553, 0.13979047848408885, 0.0742785001701673, 0.04399835661136439] | 846059 | 570269 |
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- | 1.9177 | 17.0 | 437954 | 2.1063 | 0.0757 | [0.37017425883954735, 0.13833476986726426, 0.07389756751525232, 0.04386076232849102]| 0.6671 | 0.7118 | 602265 | 846059 |
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- | 1.9265 | 18.0 | 463716 | 2.1016 | 0.0717 | [0.37650650333865443, 0.14089062050951845, 0.075366455530664, 0.045028150012067114]| 0.6192 | 0.6760 | 571937 | 846059 |
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- | 1.9622 | 19.0 | 489478 | 2.1022 | 0.0730 | [0.3746837721013452, 0.1407333566053557, 0.07570910522025132, 0.045477562304123496]| 0.6288 | 0.6831 | 577906 | 846059 |
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- | 1.9192 | 20.0 | 515240 | 2.1017 | 0.0744 | [0.3738987404904811, 0.14063074178287074, 0.0757991255723879, 0.045524517425472845]| 0.6408 | 0.6920 | 585466 | 846059 |
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  ### Framework versions
 
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  metrics:
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  - name: Bleu
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  type: bleu
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+ value: 0.07436414625113424
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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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  It achieves the following results on the evaluation set:
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  - Loss: 2.1017
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  - Bleu: 0.0744
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+ - Precisions: [0.37389569483256924, 0.14063645643779682, 0.07580332788787783, 0.045527148854836816]
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+ - Brevity Penalty: 0.6407
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  - Length Ratio: 0.6920
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+ - Translation Length: 585436
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  - Reference Length: 846059
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  ## Model description
 
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  | 1.9811 | 14.0 | 360668 | 0.0718 | 0.6325 | 0.6858 | 2.1096 | [0.37342310979981247, 0.13867710694415825, 0.0736328303569596, 0.043440268414579084] | 846059 | 580256 |
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  | 1.9745 | 15.0 | 386430 | 0.0741 | 0.6592 | 0.7059 | 2.1060 | [0.36869699176985743, 0.13724429728380805, 0.07301699268383118, 0.04318353520566863] | 846059 | 597195 |
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  | 1.939 | 16.0 | 412192 | 0.0706 | 0.6166 | 0.6740 | 2.1063 | [0.37537898781101553, 0.13979047848408885, 0.0742785001701673, 0.04399835661136439] | 846059 | 570269 |
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+ | 1.9177 | 17.0 | 437954 | 0.0757 | 0.6671 | 0.7118 | 2.1063 | [0.37017425883954735, 0.13833476986726426, 0.07389756751525232, 0.04386076232849102] | 846059 | 602265 |
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+ | 1.9265 | 18.0 | 463716 | 0.0717 | 0.6192 | 0.6760 | 2.1016 | [0.37650650333865443, 0.14089062050951845, 0.075366455530664, 0.045028150012067114] | 846059 | 571937 |
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+ | 1.9622 | 19.0 | 489478 | 0.0730 | 0.6288 | 0.6831 | 2.1022 | [0.3746837721013452, 0.1407333566053557, 0.07570910522025132, 0.045477562304123496] | 846059 | 577906 |
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+ | 1.9171 | 20.0 | 515240 | 2.1017 | 0.0744 | [0.37389569483256924, 0.14063645643779682, 0.07580332788787783, 0.045527148854836816]| 0.6407 | 0.6920 | 585436 | 846059 |
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  ### Framework versions
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