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t5-large-finetuned-break-qdmr-decomposition

Text2Text Generation
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6549f45
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1 Parent(s): 0d0fb8f

removing precisions

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  1. README.md +12 -13
README.md CHANGED
@@ -33,7 +33,6 @@ This model is a fine-tuned version of [t5-large](https://huggingface.co/t5-large
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  It achieves the following results on the evaluation set:
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  - Loss: 0.1729
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  - Bleu: 0.2217
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- - Precisions: [0.928997558602713, 0.8089017135403285, 0.702859772673759, 0.6237525532535746]
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  - Brevity Penalty: 0.2926
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  - Length Ratio: 0.4487
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  - Translation Length: 108954
@@ -68,18 +67,18 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Bleu | Precisions | Brevity Penalty | Length Ratio | Translation Length | Reference Length |
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- |:-------------:|:-----:|:----:|:---------------:|:------:|:--------------------------------------------------------------------------------:|:---------------:|:------------:|:------------------:|:----------------:|
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- | No log | 1.0 | 346 | 0.2217 | 0.2190 | [0.9212396799650076, 0.7929651493459373, 0.6788405612515656, 0.5938190356122556] | 0.2973 | 0.4519 | 109738 | 242845 |
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- | 0.3597 | 2.0 | 692 | 0.1898 | 0.2213 | [0.9278319373884388, 0.8053505444154309, 0.6955454787943451, 0.6142312076867599] | 0.2944 | 0.4499 | 109245 | 242845 |
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- | 0.1943 | 3.0 | 1038 | 0.1780 | 0.2213 | [0.9274868270332188, 0.805860010851872, 0.6987019924149351, 0.6179670572886331] | 0.2936 | 0.4494 | 109125 | 242845 |
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- | 0.1943 | 4.0 | 1385 | 0.1722 | 0.2209 | [0.9296421064226247, 0.8077246177717601, 0.6996456975263051, 0.618521199103474] | 0.2926 | 0.4486 | 108943 | 242845 |
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- | 0.1588 | 5.0 | 1731 | 0.1708 | 0.2221 | [0.9263551333376084, 0.8062900028599888, 0.7016414100962206, 0.6226711690731253] | 0.2938 | 0.4495 | 109159 | 242845 |
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- | 0.1395 | 6.0 | 2077 | 0.1699 | 0.2209 | [0.9307313480922355, 0.8116381660470879, 0.7052247221178113, 0.6255682084446319] | 0.2907 | 0.4473 | 108635 | 242845 |
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- | 0.1395 | 7.0 | 2423 | 0.1699 | 0.2219 | [0.9294629418890643, 0.8099284613256393, 0.7035550704165061, 0.623971523603898] | 0.2927 | 0.4487 | 108964 | 242845 |
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- | 0.1245 | 8.0 | 2770 | 0.1717 | 0.2215 | [0.9293905921457364, 0.8091923795588686, 0.7026416387368962, 0.6239635641714353] | 0.2924 | 0.4485 | 108909 | 242845 |
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- | 0.1152 | 9.0 | 3116 | 0.1724 | 0.2215 | [0.9294489230034706, 0.8091424956007671, 0.7027003876051995, 0.6234366789280084] | 0.2924 | 0.4485 | 108914 | 242845 |
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- | 0.1152 | 9.99 | 3460 | 0.1729 | 0.2217 | [0.928997558602713, 0.8089017135403285, 0.702859772673759, 0.6237525532535746] | 0.2926 | 0.4487 | 108954 | 242845 |
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  ### Framework versions
 
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  It achieves the following results on the evaluation set:
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  - Loss: 0.1729
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  - Bleu: 0.2217
 
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  - Brevity Penalty: 0.2926
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  - Length Ratio: 0.4487
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  - Translation Length: 108954
 
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Bleu | Brevity Penalty | Length Ratio | Translation Length | Reference Length |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:---------------:|:------------:|:------------------:|:----------------:|
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+ | No log | 1.0 | 346 | 0.2217 | 0.2190 | 0.2973 | 0.4519 | 109738 | 242845 |
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+ | 0.3597 | 2.0 | 692 | 0.1898 | 0.2213 | 0.2944 | 0.4499 | 109245 | 242845 |
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+ | 0.1943 | 3.0 | 1038 | 0.1780 | 0.2213 | 0.2936 | 0.4494 | 109125 | 242845 |
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+ | 0.1943 | 4.0 | 1385 | 0.1722 | 0.2209 | 0.2926 | 0.4486 | 108943 | 242845 |
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+ | 0.1588 | 5.0 | 1731 | 0.1708 | 0.2221 | 0.2938 | 0.4495 | 109159 | 242845 |
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+ | 0.1395 | 6.0 | 2077 | 0.1699 | 0.2209 | 0.2907 | 0.4473 | 108635 | 242845 |
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+ | 0.1395 | 7.0 | 2423 | 0.1699 | 0.2219 | 0.2927 | 0.4487 | 108964 | 242845 |
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+ | 0.1245 | 8.0 | 2770 | 0.1717 | 0.2215 | 0.2924 | 0.4485 | 108909 | 242845 |
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+ | 0.1152 | 9.0 | 3116 | 0.1724 | 0.2215 | 0.2924 | 0.4485 | 108914 | 242845 |
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+ | 0.1152 | 9.99 | 3460 | 0.1729 | 0.2217 | 0.2926 | 0.4487 | 108954 | 242845 |
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  ### Framework versions