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End of training

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  1. README.md +32 -32
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4821
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- - Accuracy: 0.8500
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  ## Model description
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@@ -49,36 +49,36 @@ 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 | 1.0 | 12 | 1.3735 | 0.5500 |
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- | No log | 2.0 | 24 | 1.2275 | 0.625 |
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- | No log | 3.0 | 36 | 1.1057 | 0.6000 |
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- | No log | 4.0 | 48 | 1.0240 | 0.625 |
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- | No log | 5.0 | 60 | 0.9663 | 0.6500 |
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- | No log | 6.0 | 72 | 0.8837 | 0.5750 |
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- | No log | 7.0 | 84 | 0.8408 | 0.6500 |
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- | No log | 8.0 | 96 | 0.7787 | 0.7000 |
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- | No log | 9.0 | 108 | 0.6871 | 0.7000 |
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- | No log | 10.0 | 120 | 0.6776 | 0.625 |
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- | No log | 11.0 | 132 | 0.6296 | 0.7250 |
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- | No log | 12.0 | 144 | 0.5752 | 0.7750 |
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- | No log | 13.0 | 156 | 0.5445 | 0.8500 |
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- | No log | 14.0 | 168 | 0.6271 | 0.8000 |
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- | No log | 15.0 | 180 | 0.6693 | 0.75 |
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- | No log | 16.0 | 192 | 0.6287 | 0.7750 |
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- | No log | 17.0 | 204 | 0.5261 | 0.8000 |
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- | No log | 18.0 | 216 | 0.5372 | 0.8000 |
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- | No log | 19.0 | 228 | 0.5511 | 0.8250 |
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- | No log | 20.0 | 240 | 0.5289 | 0.7750 |
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- | No log | 21.0 | 252 | 0.5660 | 0.7750 |
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- | No log | 22.0 | 264 | 0.5051 | 0.8500 |
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- | No log | 23.0 | 276 | 0.4821 | 0.8500 |
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- | No log | 24.0 | 288 | 0.4950 | 0.8500 |
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- | No log | 25.0 | 300 | 0.4919 | 0.8500 |
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- | No log | 26.0 | 312 | 0.4974 | 0.8500 |
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- | No log | 27.0 | 324 | 0.5535 | 0.8250 |
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- | No log | 28.0 | 336 | 0.5420 | 0.8250 |
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- | No log | 29.0 | 348 | 0.5481 | 0.8250 |
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- | No log | 30.0 | 360 | 0.5431 | 0.8250 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3741
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+ - Accuracy: 0.8250
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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 | 1.0 | 12 | 1.3036 | 0.4500 |
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+ | No log | 2.0 | 24 | 1.1112 | 0.4750 |
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+ | No log | 3.0 | 36 | 1.0265 | 0.4500 |
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+ | No log | 4.0 | 48 | 1.1130 | 0.6000 |
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+ | No log | 5.0 | 60 | 0.8603 | 0.625 |
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+ | No log | 6.0 | 72 | 0.8099 | 0.7750 |
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+ | No log | 7.0 | 84 | 0.8668 | 0.7250 |
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+ | No log | 8.0 | 96 | 0.7217 | 0.8000 |
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+ | No log | 9.0 | 108 | 0.7143 | 0.8250 |
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+ | No log | 10.0 | 120 | 0.6371 | 0.8250 |
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+ | No log | 11.0 | 132 | 0.6327 | 0.7250 |
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+ | No log | 12.0 | 144 | 0.5974 | 0.75 |
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+ | No log | 13.0 | 156 | 0.5160 | 0.8000 |
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+ | No log | 14.0 | 168 | 0.5336 | 0.75 |
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+ | No log | 15.0 | 180 | 0.5201 | 0.8000 |
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+ | No log | 16.0 | 192 | 0.4121 | 0.8250 |
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+ | No log | 17.0 | 204 | 0.4145 | 0.8000 |
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+ | No log | 18.0 | 216 | 0.4475 | 0.875 |
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+ | No log | 19.0 | 228 | 0.4147 | 0.8250 |
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+ | No log | 20.0 | 240 | 0.3818 | 0.7750 |
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+ | No log | 21.0 | 252 | 0.4136 | 0.75 |
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+ | No log | 22.0 | 264 | 0.4364 | 0.75 |
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+ | No log | 23.0 | 276 | 0.4180 | 0.7250 |
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+ | No log | 24.0 | 288 | 0.4145 | 0.75 |
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+ | No log | 25.0 | 300 | 0.4141 | 0.8000 |
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+ | No log | 26.0 | 312 | 0.3948 | 0.8000 |
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+ | No log | 27.0 | 324 | 0.3930 | 0.8250 |
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+ | No log | 28.0 | 336 | 0.3851 | 0.8250 |
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+ | No log | 29.0 | 348 | 0.3745 | 0.8250 |
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+ | No log | 30.0 | 360 | 0.3741 | 0.8250 |
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  ### Framework versions
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