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scenario-TCR-XLMV-XCOPA-4_data-xcopa_all

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PyTorch
xlm-roberta
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  1. README.md +52 -35
  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: 0.5017
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- - F1: 0.4736
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  ## Model description
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@@ -51,39 +51,56 @@ 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 | 0.4967 | 0.4711 |
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- | No log | 0.77 | 10 | 0.6931 | 0.5258 | 0.5133 |
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- | No log | 1.15 | 15 | 0.6931 | 0.5433 | 0.5456 |
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- | No log | 1.54 | 20 | 0.6931 | 0.5267 | 0.5145 |
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- | No log | 1.92 | 25 | 0.6931 | 0.5208 | 0.4987 |
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- | No log | 2.31 | 30 | 0.6931 | 0.5183 | 0.4921 |
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- | No log | 2.69 | 35 | 0.6931 | 0.5242 | 0.4987 |
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- | No log | 3.08 | 40 | 0.6931 | 0.5308 | 0.5151 |
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- | No log | 3.46 | 45 | 0.6931 | 0.53 | 0.5138 |
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- | No log | 3.85 | 50 | 0.6931 | 0.4833 | 0.4737 |
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- | No log | 4.23 | 55 | 0.6931 | 0.51 | 0.4922 |
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- | No log | 4.62 | 60 | 0.6931 | 0.5008 | 0.4759 |
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- | No log | 5.0 | 65 | 0.6931 | 0.4817 | 0.4591 |
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- | No log | 5.38 | 70 | 0.6931 | 0.5133 | 0.4859 |
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- | No log | 5.77 | 75 | 0.6932 | 0.4642 | 0.4305 |
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- | No log | 6.15 | 80 | 0.6932 | 0.4783 | 0.4360 |
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- | No log | 6.54 | 85 | 0.6932 | 0.4658 | 0.4282 |
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- | No log | 6.92 | 90 | 0.6932 | 0.455 | 0.4303 |
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- | No log | 7.31 | 95 | 0.6932 | 0.4808 | 0.4578 |
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- | No log | 7.69 | 100 | 0.6931 | 0.4967 | 0.4784 |
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- | No log | 8.08 | 105 | 0.6931 | 0.5208 | 0.5081 |
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- | No log | 8.46 | 110 | 0.6931 | 0.555 | 0.5444 |
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- | No log | 8.85 | 115 | 0.6931 | 0.5508 | 0.5397 |
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- | No log | 9.23 | 120 | 0.6931 | 0.5567 | 0.5430 |
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- | No log | 9.62 | 125 | 0.6931 | 0.5458 | 0.5338 |
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- | No log | 10.0 | 130 | 0.6931 | 0.5267 | 0.5044 |
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- | No log | 10.38 | 135 | 0.6931 | 0.5175 | 0.4961 |
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- | No log | 10.77 | 140 | 0.6931 | 0.5325 | 0.5185 |
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- | No log | 11.15 | 145 | 0.6931 | 0.5283 | 0.5104 |
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- | No log | 11.54 | 150 | 0.6931 | 0.5217 | 0.5 |
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- | No log | 11.92 | 155 | 0.6931 | 0.5058 | 0.4812 |
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- | No log | 12.31 | 160 | 0.6932 | 0.5 | 0.4792 |
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- | No log | 12.69 | 165 | 0.6931 | 0.5017 | 0.4736 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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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: 0.5008
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+ - F1: 0.4628
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  ## Model description
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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 | 0.6932 | 0.4642 | 0.4462 |
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+ | No log | 0.77 | 10 | 0.6932 | 0.485 | 0.4560 |
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+ | No log | 1.15 | 15 | 0.6932 | 0.4992 | 0.4551 |
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+ | No log | 1.54 | 20 | 0.6932 | 0.4983 | 0.4467 |
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+ | No log | 1.92 | 25 | 0.6932 | 0.4958 | 0.4444 |
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+ | No log | 2.31 | 30 | 0.6932 | 0.5075 | 0.4661 |
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+ | No log | 2.69 | 35 | 0.6931 | 0.5042 | 0.4625 |
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+ | No log | 3.08 | 40 | 0.6931 | 0.4967 | 0.4597 |
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+ | No log | 3.46 | 45 | 0.6931 | 0.4908 | 0.4636 |
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+ | No log | 3.85 | 50 | 0.6932 | 0.5008 | 0.4647 |
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+ | No log | 4.23 | 55 | 0.6931 | 0.5067 | 0.4752 |
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+ | No log | 4.62 | 60 | 0.6931 | 0.5033 | 0.4688 |
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+ | No log | 5.0 | 65 | 0.6932 | 0.4875 | 0.4524 |
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+ | No log | 5.38 | 70 | 0.6932 | 0.4517 | 0.4156 |
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+ | No log | 5.77 | 75 | 0.6932 | 0.4667 | 0.4286 |
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+ | No log | 6.15 | 80 | 0.6932 | 0.4683 | 0.4334 |
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+ | No log | 6.54 | 85 | 0.6932 | 0.47 | 0.4382 |
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+ | No log | 6.92 | 90 | 0.6932 | 0.4692 | 0.4437 |
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+ | No log | 7.31 | 95 | 0.6931 | 0.4967 | 0.4766 |
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+ | No log | 7.69 | 100 | 0.6931 | 0.53 | 0.5138 |
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+ | No log | 8.08 | 105 | 0.6931 | 0.4858 | 0.4686 |
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+ | No log | 8.46 | 110 | 0.6932 | 0.4767 | 0.4452 |
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+ | No log | 8.85 | 115 | 0.6931 | 0.4617 | 0.4353 |
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+ | No log | 9.23 | 120 | 0.6931 | 0.4683 | 0.4433 |
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+ | No log | 9.62 | 125 | 0.6931 | 0.4717 | 0.4429 |
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+ | No log | 10.0 | 130 | 0.6931 | 0.4858 | 0.4630 |
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+ | No log | 10.38 | 135 | 0.6931 | 0.4983 | 0.4872 |
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+ | No log | 10.77 | 140 | 0.6931 | 0.4958 | 0.4771 |
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+ | No log | 11.15 | 145 | 0.6931 | 0.5108 | 0.4846 |
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+ | No log | 11.54 | 150 | 0.6931 | 0.5075 | 0.4784 |
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+ | No log | 11.92 | 155 | 0.6931 | 0.5267 | 0.4883 |
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+ | No log | 12.31 | 160 | 0.6931 | 0.5142 | 0.4809 |
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+ | No log | 12.69 | 165 | 0.6931 | 0.5108 | 0.4873 |
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+ | No log | 13.08 | 170 | 0.6931 | 0.5075 | 0.4829 |
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+ | No log | 13.46 | 175 | 0.6931 | 0.5042 | 0.4758 |
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+ | No log | 13.85 | 180 | 0.6931 | 0.4825 | 0.4567 |
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+ | No log | 14.23 | 185 | 0.6931 | 0.4625 | 0.4337 |
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+ | No log | 14.62 | 190 | 0.6931 | 0.4783 | 0.4528 |
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+ | No log | 15.0 | 195 | 0.6931 | 0.4767 | 0.4510 |
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+ | No log | 15.38 | 200 | 0.6931 | 0.4675 | 0.4370 |
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+ | No log | 15.77 | 205 | 0.6931 | 0.4675 | 0.4370 |
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+ | No log | 16.15 | 210 | 0.6931 | 0.465 | 0.4368 |
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+ | No log | 16.54 | 215 | 0.6931 | 0.4792 | 0.4522 |
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+ | No log | 16.92 | 220 | 0.6931 | 0.4875 | 0.4591 |
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+ | No log | 17.31 | 225 | 0.6931 | 0.4892 | 0.4628 |
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+ | No log | 17.69 | 230 | 0.6931 | 0.4933 | 0.4591 |
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+ | No log | 18.08 | 235 | 0.6931 | 0.5325 | 0.4978 |
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+ | No log | 18.46 | 240 | 0.6931 | 0.5192 | 0.4750 |
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+ | No log | 18.85 | 245 | 0.6931 | 0.5142 | 0.4836 |
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+ | No log | 19.23 | 250 | 0.6931 | 0.5008 | 0.4628 |
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  ### Framework versions
pytorch_model.bin CHANGED
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