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yemen2016
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nbbert_indirect_speech

Token Classification
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Safetensors
bert
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End of training

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  1. README.md +26 -25
  2. model.safetensors +1 -1
  3. runs/Feb06_11-53-04_393e7c5d2d13/events.out.tfevents.1738842796.393e7c5d2d13.353.0 +3 -0
  4. runs/Feb06_11-54-34_393e7c5d2d13/events.out.tfevents.1738842876.393e7c5d2d13.353.1 +3 -0
  5. runs/Feb06_11-57-21_393e7c5d2d13/events.out.tfevents.1738843044.393e7c5d2d13.353.2 +3 -0
  6. runs/Feb06_11-57-21_393e7c5d2d13/events.out.tfevents.1738846333.393e7c5d2d13.353.3 +3 -0
  7. training_args.bin +1 -1
README.md CHANGED
@@ -21,11 +21,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [NbAiLab/nb-bert-base](https://huggingface.co/NbAiLab/nb-bert-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Accuracy: 0.8708
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- - Precision: 0.8745
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- - Recall: 0.8708
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- - F1: 0.8686
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- - Loss: 0.5487
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  ## Model description
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@@ -57,26 +57,27 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Accuracy | Precision | Recall | F1 | Validation Loss |
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- |:-------------:|:-------:|:----:|:--------:|:---------:|:------:|:------:|:---------------:|
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- | No log | 1.0 | 9 | 0.6476 | 0.6341 | 0.6476 | 0.6206 | 0.8292 |
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- | No log | 2.0 | 18 | 0.6609 | 0.7996 | 0.6609 | 0.6488 | 1.1096 |
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- | No log | 3.0 | 27 | 0.8220 | 0.8311 | 0.8220 | 0.8190 | 0.5277 |
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- | No log | 4.0 | 36 | 0.8141 | 0.8269 | 0.8141 | 0.8130 | 0.5515 |
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- | No log | 5.0 | 45 | 0.8640 | 0.8576 | 0.8640 | 0.8602 | 0.4228 |
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- | No log | 6.0 | 54 | 0.8452 | 0.8405 | 0.8452 | 0.8395 | 0.4687 |
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- | No log | 7.0 | 63 | 0.8682 | 0.8654 | 0.8682 | 0.8650 | 0.4290 |
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- | No log | 8.0 | 72 | 0.8369 | 0.8519 | 0.8369 | 0.8353 | 0.5180 |
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- | No log | 9.0 | 81 | 0.8526 | 0.8581 | 0.8526 | 0.8515 | 0.5037 |
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- | No log | 10.0 | 90 | 0.8455 | 0.8575 | 0.8455 | 0.8441 | 0.5293 |
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- | No log | 11.0 | 99 | 0.8766 | 0.8762 | 0.8766 | 0.8742 | 0.4596 |
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- | No log | 12.0 | 108 | 0.8624 | 0.8671 | 0.8624 | 0.8602 | 0.5532 |
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- | No log | 13.0 | 117 | 0.8650 | 0.8688 | 0.8650 | 0.8630 | 0.5098 |
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- | No log | 14.0 | 126 | 0.8661 | 0.8705 | 0.8661 | 0.8651 | 0.5241 |
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- | No log | 15.0 | 135 | 0.8681 | 0.8718 | 0.8681 | 0.8660 | 0.5493 |
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- | No log | 16.0 | 144 | 0.8748 | 0.8771 | 0.8748 | 0.8731 | 0.5244 |
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- | No log | 17.0 | 153 | 0.8703 | 0.8749 | 0.8703 | 0.8683 | 0.5509 |
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- | No log | 17.8235 | 160 | 0.8708 | 0.8745 | 0.8708 | 0.8686 | 0.5487 |
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [NbAiLab/nb-bert-base](https://huggingface.co/NbAiLab/nb-bert-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Accuracy: 0.8516
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+ - Precision: 0.8584
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+ - Recall: 0.8516
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+ - F1: 0.8481
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+ - Loss: 0.5580
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Accuracy | Precision | Recall | F1 | Validation Loss |
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+ |:-------------:|:-----:|:----:|:--------:|:---------:|:------:|:------:|:---------------:|
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+ | No log | 1.0 | 13 | 0.5603 | 0.6393 | 0.5603 | 0.4202 | 0.8848 |
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+ | No log | 2.0 | 26 | 0.7465 | 0.7387 | 0.7465 | 0.7388 | 0.6107 |
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+ | No log | 3.0 | 39 | 0.7477 | 0.7414 | 0.7477 | 0.7442 | 0.7030 |
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+ | No log | 4.0 | 52 | 0.7981 | 0.7980 | 0.7981 | 0.7945 | 0.5344 |
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+ | No log | 5.0 | 65 | 0.8123 | 0.8183 | 0.8123 | 0.8087 | 0.4756 |
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+ | No log | 6.0 | 78 | 0.7888 | 0.7790 | 0.7888 | 0.7818 | 0.5430 |
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+ | No log | 7.0 | 91 | 0.8123 | 0.8030 | 0.8123 | 0.8075 | 0.5115 |
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+ | No log | 8.0 | 104 | 0.8066 | 0.8012 | 0.8066 | 0.8021 | 0.5513 |
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+ | No log | 9.0 | 117 | 0.8370 | 0.8456 | 0.8370 | 0.8371 | 0.4638 |
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+ | No log | 10.0 | 130 | 0.8421 | 0.8377 | 0.8421 | 0.8379 | 0.5429 |
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+ | No log | 11.0 | 143 | 0.8519 | 0.8554 | 0.8519 | 0.8496 | 0.4703 |
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+ | No log | 12.0 | 156 | 0.8480 | 0.8428 | 0.8480 | 0.8437 | 0.5025 |
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+ | No log | 13.0 | 169 | 0.8504 | 0.8607 | 0.8504 | 0.8499 | 0.5898 |
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+ | No log | 14.0 | 182 | 0.8409 | 0.8342 | 0.8409 | 0.8366 | 0.5546 |
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+ | No log | 15.0 | 195 | 0.8365 | 0.8335 | 0.8365 | 0.8339 | 0.5665 |
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+ | No log | 16.0 | 208 | 0.8489 | 0.8503 | 0.8489 | 0.8463 | 0.5506 |
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+ | No log | 17.0 | 221 | 0.8553 | 0.8642 | 0.8553 | 0.8521 | 0.5503 |
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+ | No log | 18.0 | 234 | 0.8511 | 0.8577 | 0.8511 | 0.8476 | 0.5557 |
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+ | No log | 18.48 | 240 | 0.8516 | 0.8584 | 0.8516 | 0.8481 | 0.5580 |
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  ### Framework versions
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