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joshcarp
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gpt2-evy

Text Generation
Transformers
Safetensors
gpt2
Generated from Trainer
text-generation-inference
Inference Endpoints
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  1. README.md +105 -14
  2. model.safetensors +1 -1
README.md CHANGED
@@ -1,15 +1,11 @@
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  ---
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  license: mit
 
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  tags:
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  - generated_from_trainer
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- base_model: gpt2
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  model-index:
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  - name: gpt2-evy
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  results: []
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- widget:
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- - text: "func fizzbuzz:[]string n:num"
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- - text: "func lengthOfLongestSubstring:num s:string"
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- - text: "func fibonacci:num n:num"
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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
@@ -17,9 +13,9 @@ should probably proofread and complete it, then remove this comment. -->
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  # gpt2-evy
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- This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.6979
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  ## Model description
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@@ -44,22 +40,117 @@ 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: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | No log | 1.0 | 19 | 1.6965 |
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- | No log | 2.0 | 38 | 1.6405 |
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- | No log | 3.0 | 57 | 1.6798 |
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- | No log | 4.0 | 76 | 1.6933 |
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- | No log | 5.0 | 95 | 1.6979 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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  - Transformers 4.40.1
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- - Pytorch 2.0.1+cu117
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  - Datasets 2.19.1
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  - Tokenizers 0.19.1
 
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  ---
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  license: mit
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+ base_model: joshcarp/gpt2-evy
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  tags:
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  - generated_from_trainer
 
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  model-index:
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  - name: gpt2-evy
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  results: []
 
 
 
 
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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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  # gpt2-evy
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+ This model is a fine-tuned version of [joshcarp/gpt2-evy](https://huggingface.co/joshcarp/gpt2-evy) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.3017
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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: 100
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | No log | 1.0 | 19 | 1.9775 |
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+ | No log | 2.0 | 38 | 2.0492 |
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+ | No log | 3.0 | 57 | 2.0643 |
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+ | No log | 4.0 | 76 | 2.0102 |
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+ | No log | 5.0 | 95 | 1.9851 |
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+ | 0.0382 | 6.0 | 114 | 1.9408 |
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+ | 0.0382 | 7.0 | 133 | 2.0678 |
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+ | 0.0382 | 8.0 | 152 | 2.0022 |
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+ | 0.0382 | 9.0 | 171 | 2.0112 |
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+ | 0.0382 | 10.0 | 190 | 2.0664 |
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+ | 0.0406 | 11.0 | 209 | 2.0646 |
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+ | 0.0406 | 12.0 | 228 | 2.0033 |
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+ | 0.0406 | 13.0 | 247 | 2.0783 |
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+ | 0.0406 | 14.0 | 266 | 2.0601 |
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+ | 0.0406 | 15.0 | 285 | 2.0172 |
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+ | 0.0381 | 16.0 | 304 | 2.0543 |
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+ | 0.0381 | 17.0 | 323 | 2.1309 |
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+ | 0.0381 | 18.0 | 342 | 2.0796 |
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+ | 0.0381 | 19.0 | 361 | 2.0456 |
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+ | 0.0381 | 20.0 | 380 | 2.1159 |
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+ | 0.0381 | 21.0 | 399 | 2.0979 |
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+ | 0.0324 | 22.0 | 418 | 2.0862 |
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+ | 0.0324 | 23.0 | 437 | 2.1196 |
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+ | 0.0324 | 24.0 | 456 | 2.1273 |
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+ | 0.0324 | 25.0 | 475 | 2.1860 |
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+ | 0.0324 | 26.0 | 494 | 2.0690 |
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+ | 0.0252 | 27.0 | 513 | 2.1172 |
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+ | 0.0252 | 28.0 | 532 | 2.1453 |
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+ | 0.0252 | 29.0 | 551 | 2.0990 |
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+ | 0.0252 | 30.0 | 570 | 2.1250 |
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+ | 0.0252 | 31.0 | 589 | 2.1265 |
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+ | 0.0256 | 32.0 | 608 | 2.1649 |
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+ | 0.0256 | 33.0 | 627 | 2.1238 |
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+ | 0.0256 | 34.0 | 646 | 2.1757 |
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+ | 0.0256 | 35.0 | 665 | 2.1402 |
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+ | 0.0256 | 36.0 | 684 | 2.1569 |
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+ | 0.0239 | 37.0 | 703 | 2.1783 |
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+ | 0.0239 | 38.0 | 722 | 2.1934 |
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+ | 0.0239 | 39.0 | 741 | 2.1883 |
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+ | 0.0239 | 40.0 | 760 | 2.1831 |
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+ | 0.0239 | 41.0 | 779 | 2.1931 |
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+ | 0.0239 | 42.0 | 798 | 2.1697 |
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+ | 0.0222 | 43.0 | 817 | 2.1629 |
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+ | 0.0222 | 44.0 | 836 | 2.2133 |
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+ | 0.0222 | 45.0 | 855 | 2.1917 |
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+ | 0.0222 | 46.0 | 874 | 2.1547 |
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+ | 0.0222 | 47.0 | 893 | 2.1826 |
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+ | 0.0208 | 48.0 | 912 | 2.2125 |
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+ | 0.0208 | 49.0 | 931 | 2.2529 |
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+ | 0.0208 | 50.0 | 950 | 2.2400 |
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+ | 0.0208 | 51.0 | 969 | 2.2202 |
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+ | 0.0208 | 52.0 | 988 | 2.2158 |
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+ | 0.017 | 53.0 | 1007 | 2.2075 |
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+ | 0.017 | 54.0 | 1026 | 2.2320 |
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+ | 0.017 | 55.0 | 1045 | 2.2138 |
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+ | 0.017 | 56.0 | 1064 | 2.2015 |
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+ | 0.017 | 57.0 | 1083 | 2.2282 |
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+ | 0.0169 | 58.0 | 1102 | 2.2591 |
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+ | 0.0169 | 59.0 | 1121 | 2.2483 |
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+ | 0.0169 | 60.0 | 1140 | 2.2194 |
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+ | 0.0169 | 61.0 | 1159 | 2.2324 |
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+ | 0.0169 | 62.0 | 1178 | 2.2649 |
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+ | 0.0169 | 63.0 | 1197 | 2.2763 |
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+ | 0.0145 | 64.0 | 1216 | 2.2876 |
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+ | 0.0145 | 65.0 | 1235 | 2.2645 |
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+ | 0.0145 | 66.0 | 1254 | 2.2531 |
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+ | 0.0145 | 67.0 | 1273 | 2.2532 |
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+ | 0.0145 | 68.0 | 1292 | 2.2602 |
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+ | 0.0155 | 69.0 | 1311 | 2.2659 |
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+ | 0.0155 | 70.0 | 1330 | 2.2894 |
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+ | 0.0155 | 71.0 | 1349 | 2.2998 |
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+ | 0.0155 | 72.0 | 1368 | 2.2802 |
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+ | 0.0155 | 73.0 | 1387 | 2.2498 |
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+ | 0.0148 | 74.0 | 1406 | 2.2602 |
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+ | 0.0148 | 75.0 | 1425 | 2.2659 |
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+ | 0.0148 | 76.0 | 1444 | 2.2762 |
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+ | 0.0148 | 77.0 | 1463 | 2.2825 |
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+ | 0.0148 | 78.0 | 1482 | 2.2939 |
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+ | 0.014 | 79.0 | 1501 | 2.3115 |
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+ | 0.014 | 80.0 | 1520 | 2.3008 |
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+ | 0.014 | 81.0 | 1539 | 2.3054 |
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+ | 0.014 | 82.0 | 1558 | 2.2930 |
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+ | 0.014 | 83.0 | 1577 | 2.2872 |
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+ | 0.014 | 84.0 | 1596 | 2.2896 |
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+ | 0.014 | 85.0 | 1615 | 2.2853 |
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+ | 0.014 | 86.0 | 1634 | 2.2755 |
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+ | 0.014 | 87.0 | 1653 | 2.2781 |
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+ | 0.014 | 88.0 | 1672 | 2.2842 |
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+ | 0.014 | 89.0 | 1691 | 2.2788 |
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+ | 0.0129 | 90.0 | 1710 | 2.2850 |
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+ | 0.0129 | 91.0 | 1729 | 2.2908 |
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+ | 0.0129 | 92.0 | 1748 | 2.2964 |
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+ | 0.0129 | 93.0 | 1767 | 2.2966 |
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+ | 0.0129 | 94.0 | 1786 | 2.2975 |
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+ | 0.0121 | 95.0 | 1805 | 2.3019 |
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+ | 0.0121 | 96.0 | 1824 | 2.2990 |
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+ | 0.0121 | 97.0 | 1843 | 2.2985 |
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+ | 0.0121 | 98.0 | 1862 | 2.3000 |
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+ | 0.0121 | 99.0 | 1881 | 2.3014 |
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+ | 0.0121 | 100.0 | 1900 | 2.3017 |
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  ### Framework versions
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  - Transformers 4.40.1
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+ - Pytorch 2.2.1+cu121
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  - Datasets 2.19.1
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  - Tokenizers 0.19.1
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