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ExHubert-fine-tuned-persian_v2

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navidved/ExHubert-fine-tuned-persian-v2

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  1. README.md +21 -21
  2. model.safetensors +1 -1
  3. runs/Jan04_12-33-47_aa9869be0249/events.out.tfevents.1735994029.aa9869be0249.567.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -21,17 +21,17 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [amiriparian/ExHuBERT](https://huggingface.co/amiriparian/ExHuBERT) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6595
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- - Accuracy: 0.8160
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- - Precision: 0.8627
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- - Recall: 0.6471
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- - F1: 0.7395
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- - Precision Neutral: 0.7957
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- - Recall Neutral: 0.9303
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- - F1 Neutral: 0.8578
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- - Precision Anger: 0.8627
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- - Recall Anger: 0.6471
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- - F1 Anger: 0.7395
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  ## Model description
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@@ -63,16 +63,16 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Precision Neutral | Recall Neutral | F1 Neutral | Precision Anger | Recall Anger | F1 Anger |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-----------------:|:--------------:|:----------:|:---------------:|:------------:|:--------:|
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- | 0.6249 | 1.0 | 337 | 0.5633 | 0.7953 | 0.8602 | 0.5882 | 0.6987 | 0.7705 | 0.9353 | 0.8449 | 0.8602 | 0.5882 | 0.6987 |
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- | 0.4361 | 2.0 | 674 | 0.6575 | 0.7923 | 0.8511 | 0.5882 | 0.6957 | 0.7695 | 0.9303 | 0.8423 | 0.8511 | 0.5882 | 0.6957 |
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- | 0.3807 | 3.0 | 1011 | 0.6459 | 0.7923 | 0.6737 | 0.9412 | 0.7853 | 0.9456 | 0.6915 | 0.7989 | 0.6737 | 0.9412 | 0.7853 |
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- | 0.3778 | 4.0 | 1348 | 0.5804 | 0.8042 | 0.9070 | 0.5735 | 0.7027 | 0.7689 | 0.9602 | 0.8540 | 0.9070 | 0.5735 | 0.7027 |
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- | 0.3353 | 5.0 | 1685 | 0.6511 | 0.7745 | 0.8846 | 0.5074 | 0.6449 | 0.7413 | 0.9552 | 0.8348 | 0.8846 | 0.5074 | 0.6449 |
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- | 0.3446 | 6.0 | 2022 | 0.5828 | 0.8042 | 0.7273 | 0.8235 | 0.7724 | 0.8689 | 0.7910 | 0.8281 | 0.7273 | 0.8235 | 0.7724 |
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- | 0.2655 | 7.0 | 2359 | 0.6738 | 0.7953 | 0.8681 | 0.5809 | 0.6960 | 0.7683 | 0.9403 | 0.8456 | 0.8681 | 0.5809 | 0.6960 |
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- | 0.2426 | 8.0 | 2696 | 0.6541 | 0.8101 | 0.8158 | 0.6838 | 0.744 | 0.8072 | 0.8955 | 0.8491 | 0.8158 | 0.6838 | 0.744 |
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- | 0.1998 | 9.0 | 3033 | 0.6532 | 0.8190 | 0.8641 | 0.6544 | 0.7448 | 0.7991 | 0.9303 | 0.8598 | 0.8641 | 0.6544 | 0.7448 |
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- | 0.3289 | 10.0 | 3370 | 0.6595 | 0.8160 | 0.8627 | 0.6471 | 0.7395 | 0.7957 | 0.9303 | 0.8578 | 0.8627 | 0.6471 | 0.7395 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [amiriparian/ExHuBERT](https://huggingface.co/amiriparian/ExHuBERT) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5637
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+ - Accuracy: 0.8444
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+ - Precision: 0.8209
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+ - Recall: 0.7483
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+ - F1: 0.7829
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+ - Precision Neutral: 0.8566
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+ - Recall Neutral: 0.9020
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+ - F1 Neutral: 0.8787
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+ - Precision Anger: 0.8209
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+ - Recall Anger: 0.7483
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+ - F1 Anger: 0.7829
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Precision Neutral | Recall Neutral | F1 Neutral | Precision Anger | Recall Anger | F1 Anger |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-----------------:|:--------------:|:----------:|:---------------:|:------------:|:--------:|
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+ | 0.8717 | 1.0 | 393 | 0.7755 | 0.6454 | 0.5145 | 0.9660 | 0.6714 | 0.9569 | 0.4531 | 0.6150 | 0.5145 | 0.9660 | 0.6714 |
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+ | 0.4644 | 2.0 | 786 | 0.4577 | 0.8495 | 0.7785 | 0.8367 | 0.8066 | 0.8974 | 0.8571 | 0.8768 | 0.7785 | 0.8367 | 0.8066 |
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+ | 0.4535 | 3.0 | 1179 | 0.4818 | 0.8546 | 0.8 | 0.8163 | 0.8081 | 0.8884 | 0.8776 | 0.8830 | 0.8 | 0.8163 | 0.8081 |
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+ | 0.4773 | 4.0 | 1572 | 0.5514 | 0.8189 | 0.7289 | 0.8231 | 0.7732 | 0.8850 | 0.8163 | 0.8493 | 0.7289 | 0.8231 | 0.7732 |
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+ | 0.3337 | 5.0 | 1965 | 0.5680 | 0.8112 | 0.7417 | 0.7619 | 0.7517 | 0.8548 | 0.8408 | 0.8477 | 0.7417 | 0.7619 | 0.7517 |
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+ | 0.2774 | 6.0 | 2358 | 0.6004 | 0.8367 | 0.8879 | 0.6463 | 0.7480 | 0.8175 | 0.9510 | 0.8792 | 0.8879 | 0.6463 | 0.7480 |
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+ | 0.2007 | 7.0 | 2751 | 0.5529 | 0.8546 | 0.8629 | 0.7279 | 0.7897 | 0.8507 | 0.9306 | 0.8889 | 0.8629 | 0.7279 | 0.7897 |
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+ | 0.2025 | 8.0 | 3144 | 0.5655 | 0.8444 | 0.8162 | 0.7551 | 0.7845 | 0.8594 | 0.8980 | 0.8782 | 0.8162 | 0.7551 | 0.7845 |
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+ | 0.2583 | 9.0 | 3537 | 0.5635 | 0.8444 | 0.8258 | 0.7415 | 0.7814 | 0.8538 | 0.9061 | 0.8792 | 0.8258 | 0.7415 | 0.7814 |
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+ | 0.3264 | 10.0 | 3930 | 0.5637 | 0.8444 | 0.8209 | 0.7483 | 0.7829 | 0.8566 | 0.9020 | 0.8787 | 0.8209 | 0.7483 | 0.7829 |
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  ### Framework versions
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