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te-zsc-synthetic

Text Classification
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roberta
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  1. README.md +26 -26
  2. logs/events.out.tfevents.1717151828.f17a8cbca9b8.406.5 +3 -0
  3. model.safetensors +1 -1
  4. training_args.bin +1 -1
README.md CHANGED
@@ -9,23 +9,23 @@ metrics:
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  - recall
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  - f1
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  model-index:
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- - name: SYN_300524_epoch_4
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  results: []
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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- # SYN_300524_epoch_4
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  This model is a fine-tuned version of [projecte-aina/roberta-base-ca-v2-cased-te](https://huggingface.co/projecte-aina/roberta-base-ca-v2-cased-te) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3377
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- - Accuracy: 0.979
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- - Precision: 0.9792
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- - Recall: 0.979
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- - F1: 0.9790
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- - Ratio: 0.489
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  ## Model description
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@@ -61,24 +61,24 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Ratio |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-----:|
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- | 0.3424 | 0.0533 | 10 | 0.3592 | 0.97 | 0.9709 | 0.97 | 0.9700 | 0.478 |
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- | 0.343 | 0.1067 | 20 | 0.3539 | 0.969 | 0.9697 | 0.969 | 0.9690 | 0.481 |
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- | 0.3239 | 0.16 | 30 | 0.3525 | 0.971 | 0.9712 | 0.971 | 0.9710 | 0.511 |
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- | 0.3667 | 0.2133 | 40 | 0.3494 | 0.977 | 0.9772 | 0.977 | 0.9770 | 0.489 |
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- | 0.3101 | 0.2667 | 50 | 0.3699 | 0.965 | 0.9662 | 0.965 | 0.9650 | 0.475 |
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- | 0.3184 | 0.32 | 60 | 0.3519 | 0.978 | 0.978 | 0.978 | 0.978 | 0.5 |
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- | 0.3275 | 0.3733 | 70 | 0.3522 | 0.974 | 0.9743 | 0.974 | 0.9740 | 0.488 |
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- | 0.3132 | 0.4267 | 80 | 0.3690 | 0.972 | 0.9728 | 0.972 | 0.9720 | 0.48 |
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- | 0.3261 | 0.48 | 90 | 0.3583 | 0.976 | 0.9765 | 0.976 | 0.9760 | 0.484 |
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- | 0.3291 | 0.5333 | 100 | 0.3494 | 0.975 | 0.9750 | 0.975 | 0.9750 | 0.495 |
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- | 0.3475 | 0.5867 | 110 | 0.3421 | 0.977 | 0.9772 | 0.977 | 0.9770 | 0.489 |
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- | 0.3212 | 0.64 | 120 | 0.3407 | 0.978 | 0.9782 | 0.978 | 0.9780 | 0.49 |
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- | 0.3645 | 0.6933 | 130 | 0.3411 | 0.978 | 0.9782 | 0.978 | 0.9780 | 0.49 |
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- | 0.3326 | 0.7467 | 140 | 0.3419 | 0.978 | 0.9782 | 0.978 | 0.9780 | 0.49 |
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- | 0.3574 | 0.8 | 150 | 0.3384 | 0.979 | 0.9792 | 0.979 | 0.9790 | 0.491 |
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- | 0.3757 | 0.8533 | 160 | 0.3388 | 0.978 | 0.9782 | 0.978 | 0.9780 | 0.49 |
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- | 0.3655 | 0.9067 | 170 | 0.3388 | 0.979 | 0.9792 | 0.979 | 0.9790 | 0.489 |
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- | 0.3202 | 0.96 | 180 | 0.3381 | 0.979 | 0.9792 | 0.979 | 0.9790 | 0.489 |
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  ### Framework versions
 
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  - recall
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  - f1
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  model-index:
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+ - name: SYN_300524_epoch_5
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  results: []
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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+ # SYN_300524_epoch_5
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  This model is a fine-tuned version of [projecte-aina/roberta-base-ca-v2-cased-te](https://huggingface.co/projecte-aina/roberta-base-ca-v2-cased-te) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3372
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+ - Accuracy: 0.98
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+ - Precision: 0.9803
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+ - Recall: 0.98
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+ - F1: 0.9800
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+ - Ratio: 0.488
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Ratio |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-----:|
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+ | 0.3174 | 0.0533 | 10 | 0.3307 | 0.984 | 0.9840 | 0.984 | 0.9840 | 0.496 |
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+ | 0.3202 | 0.1067 | 20 | 0.3258 | 0.986 | 0.9861 | 0.986 | 0.9860 | 0.494 |
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+ | 0.3016 | 0.16 | 30 | 0.3282 | 0.986 | 0.9860 | 0.986 | 0.9860 | 0.504 |
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+ | 0.3291 | 0.2133 | 40 | 0.3495 | 0.977 | 0.9774 | 0.977 | 0.9770 | 0.485 |
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+ | 0.2942 | 0.2667 | 50 | 0.3602 | 0.973 | 0.9738 | 0.973 | 0.9730 | 0.479 |
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+ | 0.3121 | 0.32 | 60 | 0.3586 | 0.973 | 0.9731 | 0.973 | 0.9730 | 0.493 |
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+ | 0.3226 | 0.3733 | 70 | 0.3736 | 0.968 | 0.9681 | 0.968 | 0.9680 | 0.508 |
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+ | 0.3226 | 0.4267 | 80 | 0.3515 | 0.979 | 0.9791 | 0.979 | 0.9790 | 0.493 |
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+ | 0.3265 | 0.48 | 90 | 0.3697 | 0.97 | 0.9706 | 0.97 | 0.9700 | 0.482 |
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+ | 0.3424 | 0.5333 | 100 | 0.3650 | 0.971 | 0.9717 | 0.971 | 0.9710 | 0.481 |
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+ | 0.3348 | 0.5867 | 110 | 0.3502 | 0.976 | 0.9760 | 0.976 | 0.9760 | 0.496 |
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+ | 0.3393 | 0.64 | 120 | 0.3441 | 0.978 | 0.9780 | 0.978 | 0.9780 | 0.496 |
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+ | 0.3421 | 0.6933 | 130 | 0.3397 | 0.979 | 0.9791 | 0.979 | 0.9790 | 0.493 |
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+ | 0.3319 | 0.7467 | 140 | 0.3412 | 0.979 | 0.9791 | 0.979 | 0.9790 | 0.493 |
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+ | 0.3554 | 0.8 | 150 | 0.3416 | 0.977 | 0.9772 | 0.977 | 0.9770 | 0.489 |
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+ | 0.3829 | 0.8533 | 160 | 0.3428 | 0.978 | 0.9785 | 0.978 | 0.9780 | 0.484 |
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+ | 0.3631 | 0.9067 | 170 | 0.3396 | 0.979 | 0.9793 | 0.979 | 0.9790 | 0.487 |
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+ | 0.3362 | 0.96 | 180 | 0.3376 | 0.98 | 0.9803 | 0.98 | 0.9800 | 0.488 |
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  ### Framework versions
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