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xlnet-base-cased-airlines-news-multi-label

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  1. README.md +74 -49
  2. model.safetensors +1 -1
  3. runs/Jun06_09-34-56_ubuntu-System-Product-Name/events.out.tfevents.1717637699.ubuntu-System-Product-Name.25730.0 +3 -0
  4. runs/Jun06_09-39-45_ubuntu-System-Product-Name/events.out.tfevents.1717637987.ubuntu-System-Product-Name.25730.1 +3 -0
  5. runs/Jun06_09-42-00_ubuntu-System-Product-Name/events.out.tfevents.1717638123.ubuntu-System-Product-Name.25730.2 +3 -0
  6. runs/Jun06_09-57-11_ubuntu-System-Product-Name/events.out.tfevents.1717639032.ubuntu-System-Product-Name.25730.3 +3 -0
  7. runs/Jun06_09-59-43_ubuntu-System-Product-Name/events.out.tfevents.1717639183.ubuntu-System-Product-Name.124168.0 +3 -0
  8. runs/Jun06_09-59-43_ubuntu-System-Product-Name/events.out.tfevents.1717645851.ubuntu-System-Product-Name.124168.1 +3 -0
  9. training_args.bin +1 -1
README.md CHANGED
@@ -17,9 +17,9 @@ should probably proofread and complete it, then remove this comment. -->
17
 
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  This model is a fine-tuned version of [xlnet/xlnet-base-cased](https://huggingface.co/xlnet/xlnet-base-cased) on the None dataset.
19
  It achieves the following results on the evaluation set:
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- - Loss: 0.2567
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- - F1: 0.8989
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- - Roc Auc: 0.6475
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  ## Model description
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@@ -38,64 +38,89 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 7e-05
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- - train_batch_size: 12
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- - eval_batch_size: 12
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  - seed: 42
45
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_steps: 150
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- - num_epochs: 40
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc |
53
  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
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- | No log | 1.0 | 170 | 0.2834 | 0.8827 | 0.5576 |
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- | No log | 2.0 | 340 | 0.2670 | 0.8918 | 0.6102 |
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- | 0.2923 | 3.0 | 510 | 0.2567 | 0.8989 | 0.6475 |
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- | 0.2923 | 4.0 | 680 | 0.2526 | 0.8910 | 0.6685 |
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- | 0.2923 | 5.0 | 850 | 0.2512 | 0.8825 | 0.6352 |
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- | 0.2571 | 6.0 | 1020 | 0.2514 | 0.8863 | 0.6708 |
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- | 0.2571 | 7.0 | 1190 | 0.2454 | 0.8872 | 0.6490 |
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- | 0.2571 | 8.0 | 1360 | 0.2495 | 0.8884 | 0.6660 |
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- | 0.2468 | 9.0 | 1530 | 0.2467 | 0.8881 | 0.6725 |
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- | 0.2468 | 10.0 | 1700 | 0.2554 | 0.8815 | 0.6514 |
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- | 0.2468 | 11.0 | 1870 | 0.2474 | 0.8883 | 0.6603 |
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- | 0.2363 | 12.0 | 2040 | 0.2478 | 0.8912 | 0.6943 |
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- | 0.2363 | 13.0 | 2210 | 0.2492 | 0.8964 | 0.6976 |
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- | 0.2363 | 14.0 | 2380 | 0.2530 | 0.8936 | 0.7121 |
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- | 0.2332 | 15.0 | 2550 | 0.2497 | 0.8893 | 0.6830 |
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- | 0.2332 | 16.0 | 2720 | 0.2483 | 0.8922 | 0.7008 |
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- | 0.2332 | 17.0 | 2890 | 0.2489 | 0.8905 | 0.6782 |
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- | 0.23 | 18.0 | 3060 | 0.2496 | 0.8877 | 0.6927 |
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- | 0.23 | 19.0 | 3230 | 0.2494 | 0.8855 | 0.6652 |
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- | 0.23 | 20.0 | 3400 | 0.2483 | 0.8929 | 0.6903 |
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- | 0.2246 | 21.0 | 3570 | 0.2503 | 0.8902 | 0.6838 |
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- | 0.2246 | 22.0 | 3740 | 0.2506 | 0.8854 | 0.6805 |
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- | 0.2246 | 23.0 | 3910 | 0.2515 | 0.8900 | 0.6887 |
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- | 0.2214 | 24.0 | 4080 | 0.2501 | 0.8894 | 0.6773 |
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- | 0.2214 | 25.0 | 4250 | 0.2528 | 0.8878 | 0.6870 |
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- | 0.2214 | 26.0 | 4420 | 0.2519 | 0.8918 | 0.6895 |
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- | 0.2203 | 27.0 | 4590 | 0.2558 | 0.8897 | 0.6830 |
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- | 0.2203 | 28.0 | 4760 | 0.2554 | 0.8919 | 0.6952 |
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- | 0.2203 | 29.0 | 4930 | 0.2537 | 0.8957 | 0.7025 |
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- | 0.2193 | 30.0 | 5100 | 0.2513 | 0.8951 | 0.7025 |
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- | 0.2193 | 31.0 | 5270 | 0.2565 | 0.8946 | 0.7130 |
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- | 0.2193 | 32.0 | 5440 | 0.2542 | 0.8935 | 0.6960 |
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- | 0.2178 | 33.0 | 5610 | 0.2545 | 0.8970 | 0.7090 |
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- | 0.2178 | 34.0 | 5780 | 0.2546 | 0.8960 | 0.7138 |
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- | 0.2178 | 35.0 | 5950 | 0.2550 | 0.8942 | 0.7073 |
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- | 0.2173 | 36.0 | 6120 | 0.2545 | 0.8942 | 0.7073 |
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- | 0.2173 | 37.0 | 6290 | 0.2537 | 0.8925 | 0.7008 |
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- | 0.2173 | 38.0 | 6460 | 0.2541 | 0.8942 | 0.7073 |
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- | 0.2164 | 39.0 | 6630 | 0.2537 | 0.8940 | 0.7016 |
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- | 0.2164 | 40.0 | 6800 | 0.2540 | 0.8942 | 0.7073 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
94
 
95
 
96
  ### Framework versions
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98
  - Transformers 4.41.1
99
  - Pytorch 2.3.0+cu121
100
- - Datasets 2.19.2
101
  - Tokenizers 0.19.1
 
17
 
18
  This model is a fine-tuned version of [xlnet/xlnet-base-cased](https://huggingface.co/xlnet/xlnet-base-cased) on the None dataset.
19
  It achieves the following results on the evaluation set:
20
+ - Loss: 0.2250
21
+ - F1: 0.9209
22
+ - Jaccard: 0.6829
23
 
24
  ## Model description
25
 
 
38
  ### Training hyperparameters
39
 
40
  The following hyperparameters were used during training:
41
+ - learning_rate: 9e-05
42
+ - train_batch_size: 32
43
+ - eval_batch_size: 32
44
  - seed: 42
45
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
46
  - lr_scheduler_type: linear
47
  - lr_scheduler_warmup_steps: 150
48
+ - num_epochs: 65
49
 
50
  ### Training results
51
 
52
+ | Training Loss | Epoch | Step | Validation Loss | F1 | Jaccard |
53
  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
54
+ | No log | 1.0 | 57 | 0.3815 | 0.8283 | 0.4558 |
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+ | No log | 2.0 | 114 | 0.3186 | 0.8287 | 0.4602 |
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+ | No log | 3.0 | 171 | 0.2839 | 0.8781 | 0.5133 |
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+ | No log | 4.0 | 228 | 0.2660 | 0.8890 | 0.5457 |
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+ | No log | 5.0 | 285 | 0.2532 | 0.8996 | 0.5833 |
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+ | No log | 6.0 | 342 | 0.2471 | 0.8966 | 0.5745 |
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+ | No log | 7.0 | 399 | 0.2412 | 0.9066 | 0.6069 |
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+ | No log | 8.0 | 456 | 0.2393 | 0.9065 | 0.5981 |
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+ | 0.323 | 9.0 | 513 | 0.2354 | 0.9043 | 0.6025 |
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+ | 0.323 | 10.0 | 570 | 0.2340 | 0.9087 | 0.6077 |
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+ | 0.323 | 11.0 | 627 | 0.2326 | 0.9122 | 0.6283 |
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+ | 0.323 | 12.0 | 684 | 0.2305 | 0.9161 | 0.6401 |
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+ | 0.323 | 13.0 | 741 | 0.2297 | 0.9113 | 0.6350 |
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+ | 0.323 | 14.0 | 798 | 0.2284 | 0.9138 | 0.6416 |
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+ | 0.323 | 15.0 | 855 | 0.2281 | 0.9130 | 0.6497 |
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+ | 0.323 | 16.0 | 912 | 0.2248 | 0.9164 | 0.6527 |
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+ | 0.323 | 17.0 | 969 | 0.2228 | 0.9166 | 0.6527 |
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+ | 0.2463 | 18.0 | 1026 | 0.2232 | 0.9169 | 0.6586 |
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+ | 0.2463 | 19.0 | 1083 | 0.2243 | 0.9162 | 0.6571 |
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+ | 0.2463 | 20.0 | 1140 | 0.2236 | 0.9147 | 0.6519 |
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+ | 0.2463 | 21.0 | 1197 | 0.2255 | 0.9203 | 0.6637 |
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+ | 0.2463 | 22.0 | 1254 | 0.2261 | 0.9177 | 0.6556 |
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+ | 0.2463 | 23.0 | 1311 | 0.2226 | 0.9169 | 0.6637 |
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+ | 0.2463 | 24.0 | 1368 | 0.2226 | 0.9175 | 0.6718 |
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+ | 0.2463 | 25.0 | 1425 | 0.2246 | 0.9147 | 0.6571 |
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+ | 0.2463 | 26.0 | 1482 | 0.2240 | 0.9147 | 0.6637 |
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+ | 0.2313 | 27.0 | 1539 | 0.2237 | 0.9164 | 0.6622 |
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+ | 0.2313 | 28.0 | 1596 | 0.2235 | 0.9176 | 0.6711 |
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+ | 0.2313 | 29.0 | 1653 | 0.2228 | 0.9154 | 0.6689 |
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+ | 0.2313 | 30.0 | 1710 | 0.2220 | 0.9165 | 0.6748 |
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+ | 0.2313 | 31.0 | 1767 | 0.2231 | 0.9168 | 0.6696 |
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+ | 0.2313 | 32.0 | 1824 | 0.2231 | 0.9176 | 0.6718 |
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+ | 0.2313 | 33.0 | 1881 | 0.2241 | 0.9166 | 0.6704 |
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+ | 0.2313 | 34.0 | 1938 | 0.2224 | 0.9167 | 0.6704 |
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+ | 0.2313 | 35.0 | 1995 | 0.2219 | 0.9168 | 0.6748 |
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+ | 0.2248 | 36.0 | 2052 | 0.2250 | 0.9209 | 0.6829 |
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+ | 0.2248 | 37.0 | 2109 | 0.2235 | 0.9139 | 0.6593 |
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+ | 0.2248 | 38.0 | 2166 | 0.2226 | 0.9146 | 0.6659 |
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+ | 0.2248 | 39.0 | 2223 | 0.2228 | 0.9176 | 0.6748 |
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+ | 0.2248 | 40.0 | 2280 | 0.2227 | 0.9152 | 0.6637 |
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+ | 0.2248 | 41.0 | 2337 | 0.2225 | 0.9151 | 0.6652 |
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+ | 0.2248 | 42.0 | 2394 | 0.2224 | 0.9134 | 0.6593 |
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+ | 0.2248 | 43.0 | 2451 | 0.2225 | 0.9175 | 0.6748 |
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+ | 0.2201 | 44.0 | 2508 | 0.2219 | 0.9158 | 0.6637 |
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+ | 0.2201 | 45.0 | 2565 | 0.2222 | 0.9151 | 0.6659 |
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+ | 0.2201 | 46.0 | 2622 | 0.2211 | 0.9160 | 0.6681 |
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+ | 0.2201 | 47.0 | 2679 | 0.2214 | 0.9167 | 0.6696 |
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+ | 0.2201 | 48.0 | 2736 | 0.2218 | 0.9163 | 0.6681 |
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+ | 0.2201 | 49.0 | 2793 | 0.2217 | 0.9146 | 0.6615 |
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+ | 0.2201 | 50.0 | 2850 | 0.2216 | 0.9135 | 0.6593 |
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+ | 0.2201 | 51.0 | 2907 | 0.2217 | 0.9174 | 0.6770 |
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+ | 0.2201 | 52.0 | 2964 | 0.2219 | 0.9166 | 0.6755 |
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+ | 0.2162 | 53.0 | 3021 | 0.2219 | 0.9165 | 0.6748 |
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+ | 0.2162 | 54.0 | 3078 | 0.2214 | 0.9182 | 0.6814 |
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+ | 0.2162 | 55.0 | 3135 | 0.2211 | 0.9165 | 0.6792 |
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+ | 0.2162 | 56.0 | 3192 | 0.2211 | 0.9169 | 0.6748 |
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+ | 0.2162 | 57.0 | 3249 | 0.2211 | 0.9149 | 0.6726 |
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+ | 0.2162 | 58.0 | 3306 | 0.2209 | 0.9167 | 0.6814 |
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+ | 0.2162 | 59.0 | 3363 | 0.2213 | 0.9167 | 0.6726 |
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+ | 0.2162 | 60.0 | 3420 | 0.2215 | 0.9158 | 0.6726 |
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+ | 0.2162 | 61.0 | 3477 | 0.2211 | 0.9150 | 0.6681 |
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+ | 0.2157 | 62.0 | 3534 | 0.2211 | 0.9166 | 0.6748 |
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+ | 0.2157 | 63.0 | 3591 | 0.2209 | 0.9157 | 0.6770 |
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+ | 0.2157 | 64.0 | 3648 | 0.2209 | 0.9165 | 0.6748 |
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+ | 0.2157 | 65.0 | 3705 | 0.2209 | 0.9157 | 0.6726 |
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  ### Framework versions
122
 
123
  - Transformers 4.41.1
124
  - Pytorch 2.3.0+cu121
125
+ - Datasets 2.19.1
126
  - Tokenizers 0.19.1
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