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TeeA/t5-text2sql-english-unidecode

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Files changed (17) hide show
  1. README.md +12 -17
  2. config.json +1 -1
  3. model.safetensors +2 -2
  4. runs/Mar18_11-43-10_bf3d97118b80/events.out.tfevents.1710762208.bf3d97118b80.153.0 +3 -0
  5. runs/Mar18_11-43-10_bf3d97118b80/events.out.tfevents.1710762265.bf3d97118b80.153.1 +3 -0
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  9. runs/Mar18_11-54-40_bf3d97118b80/events.out.tfevents.1710762891.bf3d97118b80.153.5 +3 -0
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  14. runs/Mar18_12-08-22_bf3d97118b80/events.out.tfevents.1710763808.bf3d97118b80.153.10 +3 -0
  15. tokenizer.json +0 -207
  16. tokenizer_config.json +0 -184
  17. training_args.bin +1 -1
README.md CHANGED
@@ -17,11 +17,11 @@ should probably proofread and complete it, then remove this comment. -->
17
 
18
  This model is a fine-tuned version of [cssupport/t5-small-awesome-text-to-sql](https://huggingface.co/cssupport/t5-small-awesome-text-to-sql) on the None dataset.
19
  It achieves the following results on the evaluation set:
20
- - Loss: 0.9005
21
- - Rouge1: 0.4529
22
- - Rouge2: 0.3258
23
- - Rougel: 0.4443
24
- - Rougelsum: 0.4461
25
 
26
  ## Model description
27
 
@@ -46,28 +46,23 @@ The following hyperparameters were used during training:
46
  - 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
49
- - num_epochs: 10
50
  - mixed_precision_training: Native AMP
51
 
52
  ### Training results
53
 
54
  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
55
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
56
- | No log | 1.0 | 15 | 1.0750 | 0.4460 | 0.3140 | 0.4356 | 0.4352 |
57
- | No log | 2.0 | 30 | 1.0304 | 0.4506 | 0.3265 | 0.4404 | 0.4411 |
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- | No log | 3.0 | 45 | 0.9959 | 0.4529 | 0.3287 | 0.4438 | 0.4454 |
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- | No log | 4.0 | 60 | 0.9662 | 0.4599 | 0.3327 | 0.4487 | 0.4509 |
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- | No log | 5.0 | 75 | 0.9446 | 0.4589 | 0.3336 | 0.4498 | 0.4516 |
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- | No log | 6.0 | 90 | 0.9272 | 0.4521 | 0.3272 | 0.4424 | 0.4454 |
62
- | No log | 7.0 | 105 | 0.9151 | 0.4499 | 0.3247 | 0.4413 | 0.4440 |
63
- | No log | 8.0 | 120 | 0.9071 | 0.4510 | 0.3247 | 0.4424 | 0.4446 |
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- | No log | 9.0 | 135 | 0.9022 | 0.4529 | 0.3258 | 0.4443 | 0.4461 |
65
- | No log | 10.0 | 150 | 0.9005 | 0.4529 | 0.3258 | 0.4443 | 0.4461 |
66
 
67
 
68
  ### Framework versions
69
 
70
  - Transformers 4.38.2
71
- - Pytorch 2.1.0+cu121
72
  - Datasets 2.18.0
73
  - Tokenizers 0.15.2
 
17
 
18
  This model is a fine-tuned version of [cssupport/t5-small-awesome-text-to-sql](https://huggingface.co/cssupport/t5-small-awesome-text-to-sql) on the None dataset.
19
  It achieves the following results on the evaluation set:
20
+ - Loss: 2.0454
21
+ - Rouge1: 0.3934
22
+ - Rouge2: 0.2246
23
+ - Rougel: 0.3769
24
+ - Rougelsum: 0.3750
25
 
26
  ## Model description
27
 
 
46
  - seed: 42
47
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
48
  - lr_scheduler_type: linear
49
+ - num_epochs: 5
50
  - mixed_precision_training: Native AMP
51
 
52
  ### Training results
53
 
54
  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
55
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
56
+ | No log | 1.0 | 21 | 2.6820 | 0.3744 | 0.1996 | 0.3567 | 0.3541 |
57
+ | No log | 2.0 | 42 | 2.3569 | 0.3835 | 0.2191 | 0.3667 | 0.3651 |
58
+ | No log | 3.0 | 63 | 2.1723 | 0.3904 | 0.2216 | 0.3746 | 0.3725 |
59
+ | No log | 4.0 | 84 | 2.0758 | 0.3899 | 0.2214 | 0.3728 | 0.3708 |
60
+ | No log | 5.0 | 105 | 2.0454 | 0.3934 | 0.2246 | 0.3769 | 0.3750 |
 
 
 
 
 
61
 
62
 
63
  ### Framework versions
64
 
65
  - Transformers 4.38.2
66
+ - Pytorch 2.2.1+cu121
67
  - Datasets 2.18.0
68
  - Tokenizers 0.15.2
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