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Uzair54
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text2SQL-V1.0

Text2Text Generation
Transformers
TensorBoard
Safetensors
t5
Generated from Trainer
text-generation-inference
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  1. README.md +18 -32
  2. config.json +1 -1
  3. generation_config.json +1 -1
  4. model.safetensors +1 -1
  5. runs/Apr22_22-45-04_12febbe3b1cc/events.out.tfevents.1713825949.12febbe3b1cc.34.0 +3 -0
  6. runs/Apr22_22-47-59_12febbe3b1cc/events.out.tfevents.1713826096.12febbe3b1cc.34.1 +3 -0
  7. runs/Apr22_22-51-08_12febbe3b1cc/events.out.tfevents.1713826271.12febbe3b1cc.34.2 +3 -0
  8. tokenizer.json +1 -1
  9. training_args.bin +2 -2
README.md CHANGED
@@ -17,14 +17,14 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [yazdipour/text-to-sparql-t5-small-qald9](https://huggingface.co/yazdipour/text-to-sparql-t5-small-qald9) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0001
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  - Gen Len: 19.0
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- - P: 0.6665
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- - R: 0.1769
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- - F1: 0.4085
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- - Bleu-score: 12.0496
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- - Bleu-precisions: [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261]
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- - Bleu-bp: 0.1231
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  ## Model description
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@@ -49,38 +49,24 @@ 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: 20
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  - mixed_precision_training: Native AMP
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Gen Len | P | R | F1 | Bleu-score | Bleu-precisions | Bleu-bp |
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- |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:------:|:------:|:----------:|:----------------------------------------------------------------------------:|:-------:|
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- | No log | 1.0 | 28 | 0.2187 | 19.0 | 0.5442 | 0.1725 | 0.3510 | 9.1204 | [84.10326086956522, 63.125, 53.49264705882353, 45.75892857142857] | 0.1519 |
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- | No log | 2.0 | 56 | 0.0265 | 19.0 | 0.6848 | 0.1878 | 0.4229 | 9.2726 | [97.80907668231612, 94.84346224677716, 93.73601789709173, 92.02279202279202] | 0.0980 |
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- | No log | 3.0 | 84 | 0.0092 | 19.0 | 0.6648 | 0.1744 | 0.4063 | 11.7575 | [97.9502196193265, 97.10391822827938, 96.5376782077393, 95.69620253164557] | 0.1214 |
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- | No log | 4.0 | 112 | 0.0055 | 19.0 | 0.6571 | 0.1701 | 0.4004 | 12.1496 | [97.40259740259741, 95.97989949748744, 95.20958083832335, 94.07407407407408] | 0.1270 |
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- | No log | 5.0 | 140 | 0.0023 | 19.0 | 0.6654 | 0.1752 | 0.4070 | 11.8546 | [98.09941520467837, 97.44897959183673, 96.95121951219512, 96.21212121212122] | 0.1220 |
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- | No log | 6.0 | 168 | 0.0010 | 19.0 | 0.6665 | 0.1769 | 0.4085 | 12.0496 | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231 |
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- | No log | 7.0 | 196 | 0.0008 | 19.0 | 0.6665 | 0.1769 | 0.4085 | 12.0496 | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231 |
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- | No log | 8.0 | 224 | 0.0003 | 19.0 | 0.6665 | 0.1769 | 0.4085 | 12.0496 | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231 |
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- | No log | 9.0 | 252 | 0.0005 | 19.0 | 0.6665 | 0.1769 | 0.4085 | 12.0496 | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231 |
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- | No log | 10.0 | 280 | 0.0002 | 19.0 | 0.6665 | 0.1769 | 0.4085 | 12.0496 | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231 |
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- | No log | 11.0 | 308 | 0.0002 | 19.0 | 0.6665 | 0.1769 | 0.4085 | 12.0496 | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231 |
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- | No log | 12.0 | 336 | 0.0001 | 19.0 | 0.6665 | 0.1769 | 0.4085 | 12.0496 | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231 |
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- | No log | 13.0 | 364 | 0.0002 | 19.0 | 0.6665 | 0.1769 | 0.4085 | 12.0496 | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231 |
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- | No log | 14.0 | 392 | 0.0001 | 19.0 | 0.6665 | 0.1769 | 0.4085 | 12.0496 | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231 |
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- | No log | 15.0 | 420 | 0.0001 | 19.0 | 0.6665 | 0.1769 | 0.4085 | 12.0496 | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231 |
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- | No log | 16.0 | 448 | 0.0001 | 19.0 | 0.6665 | 0.1769 | 0.4085 | 12.0496 | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231 |
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- | No log | 17.0 | 476 | 0.0001 | 19.0 | 0.6665 | 0.1769 | 0.4085 | 12.0496 | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231 |
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- | 0.088 | 18.0 | 504 | 0.0001 | 19.0 | 0.6665 | 0.1769 | 0.4085 | 12.0496 | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231 |
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- | 0.088 | 19.0 | 532 | 0.0001 | 19.0 | 0.6665 | 0.1769 | 0.4085 | 12.0496 | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231 |
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- | 0.088 | 20.0 | 560 | 0.0001 | 19.0 | 0.6665 | 0.1769 | 0.4085 | 12.0496 | [98.39650145772595, 98.13559322033899, 97.77327935222672, 97.23618090452261] | 0.1231 |
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  ### Framework versions
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- - Transformers 4.38.1
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  - Pytorch 2.1.2
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- - Datasets 2.1.0
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  - Tokenizers 0.15.2
 
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  This model is a fine-tuned version of [yazdipour/text-to-sparql-t5-small-qald9](https://huggingface.co/yazdipour/text-to-sparql-t5-small-qald9) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1904
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  - Gen Len: 19.0
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+ - P: 0.6916
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+ - R: 0.1882
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+ - F1: 0.4284
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+ - Bleu-score: 18.7965
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+ - Bleu-precisions: [90.93198992443325, 84.87165483342436, 81.27608825283244, 77.3473407747866]
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+ - Bleu-bp: 0.2252
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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: 6
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  - mixed_precision_training: Native AMP
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Gen Len | P | R | F1 | Bleu-score | Bleu-precisions | Bleu-bp |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:------:|:------:|:----------:|:-----------------------------------------------------------------------------:|:-------:|
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+ | No log | 1.0 | 20 | 0.9776 | 19.0 | 0.5292 | 0.1024 | 0.3076 | 5.9735 | [80.91603053435115, 56.84062059238364, 43.75, 33.693693693693696] | 0.1171 |
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+ | No log | 2.0 | 40 | 0.4290 | 19.0 | 0.6499 | 0.1726 | 0.4010 | 16.8298 | [86.98903290129611, 74.29805615550755, 68.90459363957598, 63.082901554404145] | 0.2312 |
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+ | No log | 3.0 | 60 | 0.2963 | 19.0 | 0.6656 | 0.1836 | 0.4141 | 16.5278 | [88.91739353514623, 77.82729805013928, 73.36989640463132, 68.66173503698722] | 0.2151 |
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+ | No log | 4.0 | 80 | 0.2363 | 19.0 | 0.6889 | 0.1852 | 0.4255 | 18.5923 | [90.74823053589485, 84.64912280701755, 81.07784431137725, 77.24274406332454] | 0.2232 |
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+ | No log | 5.0 | 100 | 0.2048 | 19.0 | 0.6939 | 0.1885 | 0.4296 | 18.9610 | [91.04627766599597, 85.22355507088332, 81.78571428571429, 77.98165137614679] | 0.2261 |
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+ | No log | 6.0 | 120 | 0.1904 | 19.0 | 0.6916 | 0.1882 | 0.4284 | 18.7965 | [90.93198992443325, 84.87165483342436, 81.27608825283244, 77.3473407747866] | 0.2252 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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+ - Transformers 4.39.3
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  - Pytorch 2.1.2
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+ - Datasets 2.18.0
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  - Tokenizers 0.15.2
config.json CHANGED
@@ -56,7 +56,7 @@
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  }
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  },
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  "torch_dtype": "float32",
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- "transformers_version": "4.38.1",
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  "use_cache": true,
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  "vocab_size": 32128
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  }
 
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  }
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  },
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  "torch_dtype": "float32",
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+ "transformers_version": "4.39.3",
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  "use_cache": true,
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  "vocab_size": 32128
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  }
generation_config.json CHANGED
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