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scenario-TCR-XLMV-XCOPA-6_data-xcopa_all

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PyTorch
xlm-roberta
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  1. README.md +44 -44
  2. pytorch_model.bin +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -19,8 +19,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/xlm-v-base](https://huggingface.co/facebook/xlm-v-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.6931
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- - Accuracy: 0.535
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- - F1: 0.5114
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  ## Model description
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@@ -51,48 +51,48 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | No log | 0.38 | 5 | 0.6931 | 0.5317 | 0.4955 |
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- | No log | 0.77 | 10 | 0.6931 | 0.4917 | 0.4592 |
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- | No log | 1.15 | 15 | 0.6931 | 0.535 | 0.5053 |
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- | No log | 1.54 | 20 | 0.6932 | 0.4867 | 0.4643 |
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- | No log | 1.92 | 25 | 0.6931 | 0.5217 | 0.5017 |
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- | No log | 2.31 | 30 | 0.6935 | 0.4967 | 0.4655 |
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- | No log | 2.69 | 35 | 0.6930 | 0.5033 | 0.4726 |
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- | No log | 3.08 | 40 | 0.6932 | 0.49 | 0.4622 |
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- | No log | 3.46 | 45 | 0.6931 | 0.5225 | 0.4833 |
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- | No log | 3.85 | 50 | 0.6931 | 0.4983 | 0.4738 |
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- | No log | 4.23 | 55 | 0.6931 | 0.5217 | 0.4974 |
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- | No log | 4.62 | 60 | 0.6931 | 0.5475 | 0.5216 |
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- | No log | 5.0 | 65 | 0.6931 | 0.5467 | 0.5169 |
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- | No log | 5.38 | 70 | 0.6931 | 0.5425 | 0.5129 |
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- | No log | 5.77 | 75 | 0.6931 | 0.5433 | 0.5133 |
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- | No log | 6.15 | 80 | 0.6931 | 0.5417 | 0.5107 |
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- | No log | 6.54 | 85 | 0.6931 | 0.5458 | 0.5121 |
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- | No log | 6.92 | 90 | 0.6931 | 0.5417 | 0.5098 |
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- | No log | 7.31 | 95 | 0.6931 | 0.5483 | 0.5152 |
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- | No log | 7.69 | 100 | 0.6931 | 0.5525 | 0.5201 |
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- | No log | 8.08 | 105 | 0.6931 | 0.5342 | 0.5092 |
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- | No log | 8.46 | 110 | 0.6931 | 0.5158 | 0.4943 |
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- | No log | 8.85 | 115 | 0.6931 | 0.5483 | 0.5178 |
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- | No log | 9.23 | 120 | 0.6931 | 0.505 | 0.4715 |
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- | No log | 9.62 | 125 | 0.6931 | 0.4825 | 0.4440 |
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- | No log | 10.0 | 130 | 0.6931 | 0.4767 | 0.4353 |
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- | No log | 10.38 | 135 | 0.6931 | 0.4642 | 0.4315 |
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- | No log | 10.77 | 140 | 0.6931 | 0.5458 | 0.5156 |
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- | No log | 11.15 | 145 | 0.6931 | 0.54 | 0.5098 |
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- | No log | 11.54 | 150 | 0.6931 | 0.5458 | 0.5164 |
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- | No log | 11.92 | 155 | 0.6931 | 0.5442 | 0.5172 |
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- | No log | 12.31 | 160 | 0.6931 | 0.5375 | 0.5119 |
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- | No log | 12.69 | 165 | 0.6932 | 0.4667 | 0.4386 |
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- | No log | 13.08 | 170 | 0.6931 | 0.5383 | 0.5157 |
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- | No log | 13.46 | 175 | 0.6931 | 0.5375 | 0.5136 |
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- | No log | 13.85 | 180 | 0.6931 | 0.5392 | 0.5162 |
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- | No log | 14.23 | 185 | 0.6931 | 0.5392 | 0.5179 |
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- | No log | 14.62 | 190 | 0.6931 | 0.5417 | 0.5192 |
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- | No log | 15.0 | 195 | 0.6931 | 0.5392 | 0.5162 |
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- | No log | 15.38 | 200 | 0.6931 | 0.5383 | 0.5149 |
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- | No log | 15.77 | 205 | 0.6931 | 0.535 | 0.5122 |
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- | No log | 16.15 | 210 | 0.6931 | 0.535 | 0.5114 |
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  ### Framework versions
 
19
  This model is a fine-tuned version of [facebook/xlm-v-base](https://huggingface.co/facebook/xlm-v-base) on the None dataset.
20
  It achieves the following results on the evaluation set:
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  - Loss: 0.6931
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+ - Accuracy: 0.5083
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+ - F1: 0.4627
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
53
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | No log | 0.38 | 5 | 0.6931 | 0.5133 | 0.4904 |
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+ | No log | 0.77 | 10 | 0.6931 | 0.5542 | 0.5344 |
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+ | No log | 1.15 | 15 | 0.6931 | 0.5358 | 0.5093 |
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+ | No log | 1.54 | 20 | 0.6931 | 0.5508 | 0.5373 |
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+ | No log | 1.92 | 25 | 0.6931 | 0.5033 | 0.4716 |
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+ | No log | 2.31 | 30 | 0.6931 | 0.53 | 0.5261 |
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+ | No log | 2.69 | 35 | 0.6931 | 0.5383 | 0.5257 |
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+ | No log | 3.08 | 40 | 0.6931 | 0.5308 | 0.5159 |
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+ | No log | 3.46 | 45 | 0.6931 | 0.4933 | 0.4856 |
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+ | No log | 3.85 | 50 | 0.6931 | 0.5308 | 0.5233 |
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+ | No log | 4.23 | 55 | 0.6931 | 0.5517 | 0.5410 |
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+ | No log | 4.62 | 60 | 0.6931 | 0.5625 | 0.5570 |
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+ | No log | 5.0 | 65 | 0.6931 | 0.5433 | 0.5308 |
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+ | No log | 5.38 | 70 | 0.6931 | 0.53 | 0.5236 |
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+ | No log | 5.77 | 75 | 0.6931 | 0.5267 | 0.5103 |
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+ | No log | 6.15 | 80 | 0.6931 | 0.5308 | 0.4987 |
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+ | No log | 6.54 | 85 | 0.6931 | 0.5017 | 0.4889 |
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+ | No log | 6.92 | 90 | 0.6931 | 0.5267 | 0.5009 |
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+ | No log | 7.31 | 95 | 0.6931 | 0.5367 | 0.5062 |
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+ | No log | 7.69 | 100 | 0.6931 | 0.5133 | 0.4859 |
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+ | No log | 8.08 | 105 | 0.6931 | 0.4817 | 0.4610 |
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+ | No log | 8.46 | 110 | 0.6932 | 0.5 | 0.4854 |
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+ | No log | 8.85 | 115 | 0.6931 | 0.4992 | 0.4788 |
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+ | No log | 9.23 | 120 | 0.6931 | 0.5 | 0.4881 |
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+ | No log | 9.62 | 125 | 0.6931 | 0.5042 | 0.4884 |
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+ | No log | 10.0 | 130 | 0.6931 | 0.5025 | 0.4936 |
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+ | No log | 10.38 | 135 | 0.6931 | 0.4908 | 0.4764 |
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+ | No log | 10.77 | 140 | 0.6931 | 0.4942 | 0.4816 |
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+ | No log | 11.15 | 145 | 0.6932 | 0.5033 | 0.4532 |
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+ | No log | 11.54 | 150 | 0.6931 | 0.525 | 0.4732 |
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+ | No log | 11.92 | 155 | 0.6931 | 0.53 | 0.4946 |
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+ | No log | 12.31 | 160 | 0.6931 | 0.5192 | 0.4489 |
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+ | No log | 12.69 | 165 | 0.6931 | 0.5225 | 0.4729 |
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+ | No log | 13.08 | 170 | 0.6931 | 0.5117 | 0.4624 |
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+ | No log | 13.46 | 175 | 0.6931 | 0.5383 | 0.4851 |
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+ | No log | 13.85 | 180 | 0.6931 | 0.5208 | 0.4691 |
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+ | No log | 14.23 | 185 | 0.6931 | 0.5258 | 0.4717 |
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+ | No log | 14.62 | 190 | 0.6931 | 0.5417 | 0.4860 |
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+ | No log | 15.0 | 195 | 0.6931 | 0.5233 | 0.4838 |
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+ | No log | 15.38 | 200 | 0.6931 | 0.5258 | 0.4851 |
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+ | No log | 15.77 | 205 | 0.6931 | 0.5392 | 0.4931 |
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+ | No log | 16.15 | 210 | 0.6931 | 0.5083 | 0.4627 |
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  ### Framework versions
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