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lge_tests_prelim

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Safetensors
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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: 0.0000
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- - Accuracy: 1.0
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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 | 2.6916 | 0.0 |
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- | 1.9541 | 0.0320 | 100 | 1.9214 | 0.005 |
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- | 0.9728 | 0.0641 | 200 | 1.0690 | 0.0 |
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- | 0.9099 | 0.0961 | 300 | 0.7838 | 0.035 |
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- | 0.481 | 0.1281 | 400 | 0.5249 | 0.18 |
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- | 0.4591 | 0.1602 | 500 | 0.5097 | 0.235 |
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- | 0.4191 | 0.1922 | 600 | 0.5116 | 0.285 |
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- | 0.1323 | 0.2242 | 700 | 0.1011 | 0.775 |
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- | 0.0385 | 0.2562 | 800 | 0.0188 | 0.985 |
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- | 0.1343 | 0.2883 | 900 | 0.0617 | 0.86 |
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- | 0.0199 | 0.3203 | 1000 | 0.0369 | 0.91 |
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- | 0.0021 | 0.3523 | 1100 | 0.0085 | 0.98 |
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- | 0.0779 | 0.3844 | 1200 | 0.0270 | 0.945 |
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- | 0.0077 | 0.4164 | 1300 | 0.0044 | 0.995 |
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- | 0.0165 | 0.4484 | 1400 | 0.0063 | 0.99 |
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- | 0.0494 | 0.4805 | 1500 | 0.0651 | 0.87 |
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- | 0.0012 | 0.5125 | 1600 | 0.0285 | 0.975 |
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- | 0.0175 | 0.5445 | 1700 | 0.0108 | 0.99 |
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- | 0.0001 | 0.5766 | 1800 | 0.0001 | 1.0 |
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- | 0.0001 | 0.6086 | 1900 | 0.0001 | 1.0 |
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- | 0.0 | 0.6406 | 2000 | 0.0000 | 1.0 |
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- | 0.0001 | 0.6726 | 2100 | 0.0001 | 1.0 |
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- | 0.0 | 0.7047 | 2200 | 0.0000 | 1.0 |
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- | 0.0 | 0.7367 | 2300 | 0.0000 | 1.0 |
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- | 0.0 | 0.7687 | 2400 | 0.0000 | 1.0 |
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- | 0.0 | 0.8008 | 2500 | 0.0000 | 1.0 |
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- | 0.0 | 0.8328 | 2600 | 0.0000 | 1.0 |
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- | 0.0 | 0.8648 | 2700 | 0.0000 | 1.0 |
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- | 0.0 | 0.8969 | 2800 | 0.0000 | 1.0 |
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- | 0.0 | 0.9289 | 2900 | 0.0000 | 1.0 |
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- | 0.0 | 0.9609 | 3000 | 0.0000 | 1.0 |
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- | 0.0 | 0.9930 | 3100 | 0.0000 | 1.0 |
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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: 0.0077
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+ - Accuracy: 0.965
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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 | 2.7400 | 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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