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lge_tests_prelim

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  1. README.md +34 -34
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -16,8 +16,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0077
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- - Accuracy: 0.965
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  ## Model description
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@@ -49,38 +49,38 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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- | No log | 0 | 0 | 2.7400 | 0.0 |
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- | 1.936 | 0.0320 | 100 | 2.0872 | 0.0 |
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- | 1.0955 | 0.0641 | 200 | 1.4639 | 0.0 |
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- | 0.6647 | 0.0961 | 300 | 1.0303 | 0.0 |
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- | 0.3044 | 0.1281 | 400 | 0.5894 | 0.07 |
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- | 0.0784 | 0.1602 | 500 | 0.4356 | 0.125 |
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- | 0.0455 | 0.1922 | 600 | 0.3727 | 0.195 |
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- | 0.0196 | 0.2242 | 700 | 0.5933 | 0.06 |
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- | 0.0064 | 0.2562 | 800 | 0.1472 | 0.465 |
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- | 0.045 | 0.2883 | 900 | 0.7712 | 0.155 |
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- | 0.0904 | 0.3203 | 1000 | 0.6663 | 0.035 |
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- | 0.0205 | 0.3523 | 1100 | 0.6186 | 0.13 |
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- | 0.0005 | 0.3844 | 1200 | 0.1296 | 0.57 |
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- | 0.001 | 0.4164 | 1300 | 0.4545 | 0.205 |
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- | 0.0014 | 0.4484 | 1400 | 0.2325 | 0.355 |
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- | 0.0008 | 0.4805 | 1500 | 0.2777 | 0.31 |
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- | 0.0 | 0.5125 | 1600 | 0.0509 | 0.825 |
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- | 0.0 | 0.5445 | 1700 | 0.0113 | 0.955 |
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- | 0.0 | 0.5766 | 1800 | 0.0096 | 0.965 |
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- | 0.0 | 0.6086 | 1900 | 0.0090 | 0.96 |
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- | 0.0 | 0.6406 | 2000 | 0.0088 | 0.96 |
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- | 0.0 | 0.6726 | 2100 | 0.0084 | 0.96 |
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- | 0.0 | 0.7047 | 2200 | 0.0083 | 0.96 |
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- | 0.0 | 0.7367 | 2300 | 0.0081 | 0.965 |
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- | 0.0 | 0.7687 | 2400 | 0.0080 | 0.965 |
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- | 0.0 | 0.8008 | 2500 | 0.0079 | 0.965 |
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- | 0.0 | 0.8328 | 2600 | 0.0078 | 0.965 |
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- | 0.0 | 0.8648 | 2700 | 0.0078 | 0.965 |
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- | 0.0 | 0.8969 | 2800 | 0.0078 | 0.965 |
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- | 0.0 | 0.9289 | 2900 | 0.0077 | 0.965 |
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- | 0.0 | 0.9609 | 3000 | 0.0077 | 0.965 |
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- | 0.0 | 0.9930 | 3100 | 0.0077 | 0.965 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.8329
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+ - Accuracy: 0.0
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | No log | 0 | 0 | 2.8542 | 0.0 |
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+ | 1.9753 | 0.0320 | 100 | 2.2451 | 0.0 |
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+ | 1.1255 | 0.0641 | 200 | 2.2519 | 0.0 |
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+ | 0.8756 | 0.0961 | 300 | 3.2185 | 0.0 |
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+ | 0.2727 | 0.1281 | 400 | 2.4786 | 0.0 |
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+ | 0.1232 | 0.1602 | 500 | 2.3917 | 0.0 |
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+ | 0.0938 | 0.1922 | 600 | 2.6180 | 0.0 |
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+ | 0.0172 | 0.2242 | 700 | 2.5046 | 0.0 |
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+ | 0.009 | 0.2562 | 800 | 3.0210 | 0.0 |
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+ | 0.0063 | 0.2883 | 900 | 4.7522 | 0.0 |
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+ | 0.007 | 0.3203 | 1000 | 2.7294 | 0.0 |
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+ | 0.1761 | 0.3523 | 1100 | 4.3269 | 0.0 |
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+ | 0.0049 | 0.3844 | 1200 | 3.0986 | 0.0 |
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+ | 0.0531 | 0.4164 | 1300 | 2.7182 | 0.0 |
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+ | 0.0001 | 0.4484 | 1400 | 2.3752 | 0.0 |
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+ | 0.0003 | 0.4805 | 1500 | 2.1509 | 0.0 |
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+ | 0.0 | 0.5125 | 1600 | 1.9732 | 0.0 |
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+ | 0.0 | 0.5445 | 1700 | 1.9455 | 0.0 |
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+ | 0.0001 | 0.5766 | 1800 | 2.5503 | 0.0 |
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+ | 0.0 | 0.6086 | 1900 | 3.0727 | 0.0 |
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+ | 0.0 | 0.6406 | 2000 | 2.9809 | 0.0 |
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+ | 0.0 | 0.6726 | 2100 | 2.9336 | 0.0 |
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+ | 0.0 | 0.7047 | 2200 | 2.9020 | 0.0 |
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+ | 0.0 | 0.7367 | 2300 | 2.8789 | 0.0 |
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+ | 0.0 | 0.7687 | 2400 | 2.8641 | 0.0 |
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+ | 0.0 | 0.8008 | 2500 | 2.8528 | 0.0 |
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+ | 0.0 | 0.8328 | 2600 | 2.8459 | 0.0 |
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+ | 0.0 | 0.8648 | 2700 | 2.8396 | 0.0 |
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+ | 0.0 | 0.8969 | 2800 | 2.8355 | 0.0 |
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+ | 0.0 | 0.9289 | 2900 | 2.8340 | 0.0 |
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+ | 0.0 | 0.9609 | 3000 | 2.8330 | 0.0 |
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+ | 0.0 | 0.9930 | 3100 | 2.8329 | 0.0 |
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  ### Framework versions
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