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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.1717148242.f17a8cbca9b8.406.2 +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_1
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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_1
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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: 0.3748
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- - Accuracy: 0.961
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- - Precision: 0.9615
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- - Recall: 0.961
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- - F1: 0.9610
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- - Ratio: 0.483
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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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- | 2.9367 | 0.0533 | 10 | 1.4668 | 0.65 | 0.7117 | 0.65 | 0.6225 | 0.77 |
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- | 1.1009 | 0.1067 | 20 | 0.6674 | 0.856 | 0.8560 | 0.856 | 0.8560 | 0.502 |
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- | 0.6993 | 0.16 | 30 | 0.5583 | 0.908 | 0.9095 | 0.9080 | 0.9079 | 0.53 |
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- | 0.6377 | 0.2133 | 40 | 0.4923 | 0.934 | 0.9343 | 0.9340 | 0.9340 | 0.486 |
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- | 0.5192 | 0.2667 | 50 | 0.4930 | 0.926 | 0.9282 | 0.9260 | 0.9259 | 0.464 |
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- | 0.5189 | 0.32 | 60 | 0.4687 | 0.937 | 0.9383 | 0.937 | 0.9370 | 0.527 |
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- | 0.5083 | 0.3733 | 70 | 0.4321 | 0.944 | 0.9445 | 0.944 | 0.9440 | 0.484 |
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- | 0.4645 | 0.4267 | 80 | 0.4026 | 0.949 | 0.9490 | 0.949 | 0.9490 | 0.495 |
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- | 0.4268 | 0.48 | 90 | 0.3990 | 0.949 | 0.9498 | 0.9490 | 0.9490 | 0.479 |
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- | 0.4327 | 0.5333 | 100 | 0.3949 | 0.952 | 0.9524 | 0.952 | 0.9520 | 0.486 |
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- | 0.4283 | 0.5867 | 110 | 0.3894 | 0.954 | 0.9540 | 0.954 | 0.9540 | 0.496 |
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- | 0.4263 | 0.64 | 120 | 0.3829 | 0.957 | 0.9572 | 0.957 | 0.9570 | 0.489 |
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- | 0.4205 | 0.6933 | 130 | 0.3800 | 0.962 | 0.9620 | 0.962 | 0.9620 | 0.496 |
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- | 0.4291 | 0.7467 | 140 | 0.3760 | 0.962 | 0.9620 | 0.962 | 0.9620 | 0.502 |
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- | 0.4124 | 0.8 | 150 | 0.3723 | 0.964 | 0.9641 | 0.964 | 0.9640 | 0.494 |
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- | 0.4142 | 0.8533 | 160 | 0.3720 | 0.964 | 0.9641 | 0.964 | 0.9640 | 0.492 |
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- | 0.4209 | 0.9067 | 170 | 0.3767 | 0.96 | 0.9605 | 0.96 | 0.9600 | 0.484 |
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- | 0.3908 | 0.96 | 180 | 0.3748 | 0.96 | 0.9605 | 0.96 | 0.9600 | 0.484 |
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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_2
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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_2
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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: 0.3618
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+ - Accuracy: 0.972
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+ - Precision: 0.9723
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+ - Recall: 0.972
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+ - F1: 0.9720
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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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+ | 0.3977 | 0.0533 | 10 | 0.3957 | 0.951 | 0.9530 | 0.9510 | 0.9509 | 0.467 |
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+ | 0.4006 | 0.1067 | 20 | 0.3771 | 0.96 | 0.9609 | 0.96 | 0.9600 | 0.478 |
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+ | 0.3774 | 0.16 | 30 | 0.3709 | 0.963 | 0.9632 | 0.963 | 0.9630 | 0.491 |
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+ | 0.3894 | 0.2133 | 40 | 0.3956 | 0.958 | 0.9592 | 0.958 | 0.9580 | 0.474 |
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+ | 0.3423 | 0.2667 | 50 | 0.3938 | 0.96 | 0.9606 | 0.96 | 0.9600 | 0.482 |
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+ | 0.3965 | 0.32 | 60 | 0.3794 | 0.959 | 0.9597 | 0.959 | 0.9590 | 0.481 |
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+ | 0.3998 | 0.3733 | 70 | 0.3602 | 0.967 | 0.9670 | 0.967 | 0.9670 | 0.497 |
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+ | 0.3718 | 0.4267 | 80 | 0.3998 | 0.956 | 0.9576 | 0.956 | 0.9560 | 0.47 |
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+ | 0.3924 | 0.48 | 90 | 0.3829 | 0.963 | 0.9638 | 0.963 | 0.9630 | 0.479 |
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+ | 0.371 | 0.5333 | 100 | 0.3816 | 0.966 | 0.9666 | 0.966 | 0.9660 | 0.482 |
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+ | 0.3752 | 0.5867 | 110 | 0.3727 | 0.967 | 0.9675 | 0.967 | 0.9670 | 0.483 |
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+ | 0.3631 | 0.64 | 120 | 0.3669 | 0.966 | 0.9665 | 0.966 | 0.9660 | 0.484 |
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+ | 0.3934 | 0.6933 | 130 | 0.3641 | 0.968 | 0.9684 | 0.968 | 0.9680 | 0.486 |
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+ | 0.3536 | 0.7467 | 140 | 0.3588 | 0.97 | 0.9701 | 0.97 | 0.9700 | 0.494 |
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+ | 0.3542 | 0.8 | 150 | 0.3565 | 0.971 | 0.9710 | 0.971 | 0.9710 | 0.495 |
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+ | 0.3785 | 0.8533 | 160 | 0.3580 | 0.971 | 0.9711 | 0.971 | 0.9710 | 0.493 |
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+ | 0.3557 | 0.9067 | 170 | 0.3616 | 0.971 | 0.9713 | 0.971 | 0.9710 | 0.487 |
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+ | 0.3592 | 0.96 | 180 | 0.3618 | 0.972 | 0.9723 | 0.972 | 0.9720 | 0.488 |
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  ### Framework versions
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