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nhidinh2
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xlm-roberta-base-finetuned-ner-thesis-dseb

Token Classification
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xlm-roberta
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End of training

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  1. README.md +20 -20
  2. model.safetensors +1 -1
  3. runs/Jul08_04-20-07_18b6494838a7/events.out.tfevents.1720412547.18b6494838a7.274.0 +3 -0
  4. runs/Jul08_04-24-38_18b6494838a7/events.out.tfevents.1720412685.18b6494838a7.274.1 +3 -0
  5. runs/Jul08_04-24-38_18b6494838a7/events.out.tfevents.1720412902.18b6494838a7.274.2 +3 -0
  6. training_args.bin +1 -1
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1345
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- - Precision: 0.1786
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- - Recall: 0.1351
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- - F1: 0.1538
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- - Accuracy: 0.9563
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  ## Model description
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@@ -55,21 +55,21 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | 0.8175 | 1.0 | 12 | 0.3119 | 0.0 | 0.0 | 0.0 | 0.9593 |
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- | 0.2019 | 2.0 | 24 | 0.2414 | 0.0 | 0.0 | 0.0 | 0.9593 |
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- | 0.1156 | 3.0 | 36 | 0.2105 | 0.0 | 0.0 | 0.0 | 0.9593 |
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- | 0.0913 | 4.0 | 48 | 0.1831 | 0.0 | 0.0 | 0.0 | 0.9593 |
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- | 0.0987 | 5.0 | 60 | 0.1695 | 0.0 | 0.0 | 0.0 | 0.9593 |
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- | 0.0697 | 6.0 | 72 | 0.1727 | 0.0 | 0.0 | 0.0 | 0.9593 |
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- | 0.0528 | 7.0 | 84 | 0.1462 | 0.0 | 0.0 | 0.0 | 0.9593 |
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- | 0.0538 | 8.0 | 96 | 0.1441 | 0.0 | 0.0 | 0.0 | 0.9593 |
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- | 0.0504 | 9.0 | 108 | 0.1854 | 0.0 | 0.0 | 0.0 | 0.9605 |
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- | 0.0359 | 10.0 | 120 | 0.1516 | 0.0476 | 0.0312 | 0.0377 | 0.9641 |
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- | 0.031 | 11.0 | 132 | 0.1836 | 0.0 | 0.0 | 0.0 | 0.9621 |
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- | 0.038 | 12.0 | 144 | 0.1581 | 0.1579 | 0.0938 | 0.1176 | 0.9627 |
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- | 0.0349 | 13.0 | 156 | 0.1901 | 0.0 | 0.0 | 0.0 | 0.9625 |
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- | 0.0226 | 14.0 | 168 | 0.1740 | 0.0667 | 0.0312 | 0.0426 | 0.9648 |
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- | 0.0198 | 15.0 | 180 | 0.1729 | 0.125 | 0.0625 | 0.0833 | 0.9639 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1090
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+ - Precision: 0.4
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+ - Recall: 0.7143
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+ - F1: 0.5128
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+ - Accuracy: 0.9819
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.0555 | 1.0 | 50 | 0.3106 | 0.0 | 0.0 | 0.0 | 0.9466 |
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+ | 0.0994 | 2.0 | 100 | 0.2248 | 0.0 | 0.0 | 0.0 | 0.9466 |
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+ | 0.0567 | 3.0 | 150 | 0.1854 | 0.0 | 0.0 | 0.0 | 0.9466 |
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+ | 0.0361 | 4.0 | 200 | 0.2000 | 0.0 | 0.0 | 0.0 | 0.9509 |
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+ | 0.0449 | 5.0 | 250 | 0.3142 | 0.0 | 0.0 | 0.0 | 0.9534 |
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+ | 0.0115 | 6.0 | 300 | 0.1578 | 0.3182 | 0.35 | 0.3333 | 0.9671 |
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+ | 0.0029 | 7.0 | 350 | 0.2387 | 0.5417 | 0.325 | 0.4062 | 0.9619 |
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+ | 0.0096 | 8.0 | 400 | 0.3105 | 0.4 | 0.2 | 0.2667 | 0.9572 |
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+ | 0.0011 | 9.0 | 450 | 0.2763 | 0.3571 | 0.25 | 0.2941 | 0.9611 |
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+ | 0.0015 | 10.0 | 500 | 0.2726 | 0.4286 | 0.3 | 0.3529 | 0.9624 |
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+ | 0.0017 | 11.0 | 550 | 0.2226 | 0.3529 | 0.3 | 0.3243 | 0.9633 |
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+ | 0.0016 | 12.0 | 600 | 0.2720 | 0.3704 | 0.25 | 0.2985 | 0.9606 |
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+ | 0.0003 | 13.0 | 650 | 0.3011 | 0.4091 | 0.225 | 0.2903 | 0.9593 |
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+ | 0.0012 | 14.0 | 700 | 0.2753 | 0.36 | 0.225 | 0.2769 | 0.9613 |
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+ | 0.0042 | 15.0 | 750 | 0.2507 | 0.4074 | 0.275 | 0.3284 | 0.9633 |
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  ### Framework versions
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