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trainer_4f

Text Classification
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distilbert
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End of training

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  1. README.md +22 -22
  2. model.safetensors +1 -1
  3. runs/Apr09_10-52-53_4e87a2fad7e9/events.out.tfevents.1712659976.4e87a2fad7e9.357.0 +3 -0
  4. runs/Apr09_10-52-53_4e87a2fad7e9/events.out.tfevents.1712668956.4e87a2fad7e9.357.1 +3 -0
  5. 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 [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8702
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- - Precision: 0.8515
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- - Recall: 0.8466
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- - F1: 0.8470
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- - Accuracy: 0.8466
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  ## Model description
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@@ -55,23 +55,23 @@ 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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- | 1.533 | 0.28 | 100 | 1.0530 | 0.7000 | 0.6596 | 0.6446 | 0.6596 |
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- | 0.7719 | 0.56 | 200 | 0.6741 | 0.8161 | 0.8042 | 0.8048 | 0.8042 |
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- | 0.6263 | 0.84 | 300 | 0.6786 | 0.8341 | 0.8042 | 0.8048 | 0.8042 |
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- | 0.4594 | 1.12 | 400 | 0.6451 | 0.8241 | 0.8166 | 0.8166 | 0.8166 |
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- | 0.3493 | 1.4 | 500 | 0.6712 | 0.8407 | 0.8307 | 0.8320 | 0.8307 |
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- | 0.4026 | 1.69 | 600 | 0.7157 | 0.8566 | 0.8430 | 0.8449 | 0.8430 |
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- | 0.2855 | 1.97 | 700 | 0.6660 | 0.8443 | 0.8377 | 0.8389 | 0.8377 |
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- | 0.2064 | 2.25 | 800 | 0.7002 | 0.8538 | 0.8466 | 0.8475 | 0.8466 |
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- | 0.1696 | 2.53 | 900 | 0.8148 | 0.8381 | 0.8325 | 0.8339 | 0.8325 |
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- | 0.2012 | 2.81 | 1000 | 0.8666 | 0.8188 | 0.8166 | 0.8168 | 0.8166 |
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- | 0.1659 | 3.09 | 1100 | 0.8505 | 0.8288 | 0.8272 | 0.8270 | 0.8272 |
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- | 0.072 | 3.37 | 1200 | 0.8390 | 0.8580 | 0.8501 | 0.8512 | 0.8501 |
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- | 0.0961 | 3.65 | 1300 | 0.8345 | 0.8552 | 0.8483 | 0.8492 | 0.8483 |
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- | 0.0591 | 3.93 | 1400 | 0.8653 | 0.8551 | 0.8466 | 0.8477 | 0.8466 |
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- | 0.0412 | 4.21 | 1500 | 0.8634 | 0.8511 | 0.8466 | 0.8470 | 0.8466 |
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- | 0.0579 | 4.49 | 1600 | 0.8721 | 0.8486 | 0.8448 | 0.8450 | 0.8448 |
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- | 0.0306 | 4.78 | 1700 | 0.8699 | 0.8486 | 0.8448 | 0.8450 | 0.8448 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.8577
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+ - Precision: 0.8485
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+ - Recall: 0.8430
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+ - F1: 0.8432
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+ - Accuracy: 0.8430
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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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+ | 1.652 | 0.28 | 100 | 1.1388 | 0.6937 | 0.6437 | 0.6307 | 0.6437 |
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+ | 0.859 | 0.56 | 200 | 0.7035 | 0.8068 | 0.7919 | 0.7899 | 0.7919 |
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+ | 0.6338 | 0.84 | 300 | 0.6473 | 0.8388 | 0.8113 | 0.8127 | 0.8113 |
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+ | 0.4787 | 1.12 | 400 | 0.6436 | 0.8229 | 0.8131 | 0.8129 | 0.8131 |
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+ | 0.4248 | 1.4 | 500 | 0.6372 | 0.8328 | 0.8289 | 0.8286 | 0.8289 |
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+ | 0.4081 | 1.69 | 600 | 0.5920 | 0.8599 | 0.8554 | 0.8554 | 0.8554 |
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+ | 0.2712 | 1.97 | 700 | 0.6843 | 0.8466 | 0.8413 | 0.8421 | 0.8413 |
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+ | 0.1995 | 2.25 | 800 | 0.6760 | 0.8552 | 0.8448 | 0.8461 | 0.8448 |
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+ | 0.2102 | 2.53 | 900 | 0.7538 | 0.8424 | 0.8377 | 0.8387 | 0.8377 |
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+ | 0.204 | 2.81 | 1000 | 0.7491 | 0.8374 | 0.8325 | 0.8327 | 0.8325 |
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+ | 0.1359 | 3.09 | 1100 | 0.7597 | 0.8537 | 0.8483 | 0.8480 | 0.8483 |
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+ | 0.0688 | 3.37 | 1200 | 0.8339 | 0.8405 | 0.8342 | 0.8338 | 0.8342 |
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+ | 0.0878 | 3.65 | 1300 | 0.8136 | 0.8545 | 0.8466 | 0.8465 | 0.8466 |
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+ | 0.0795 | 3.93 | 1400 | 0.8346 | 0.8435 | 0.8395 | 0.8397 | 0.8395 |
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+ | 0.0256 | 4.21 | 1500 | 0.8602 | 0.8417 | 0.8360 | 0.8362 | 0.8360 |
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+ | 0.0589 | 4.49 | 1600 | 0.8559 | 0.8507 | 0.8448 | 0.8449 | 0.8448 |
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+ | 0.0201 | 4.78 | 1700 | 0.8603 | 0.8500 | 0.8448 | 0.8449 | 0.8448 |
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  ### Framework versions
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