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wav2vec2-classifier-aug

Audio Classification
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
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  1. README.md +58 -58
  2. runs/Jun21_11-51-34_LAPTOP-1GID9RGH/events.out.tfevents.1718945495.LAPTOP-1GID9RGH.7328.0 +2 -2
README.md CHANGED
@@ -20,12 +20,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.9532
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- - Accuracy: 0.7951
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- - Precision: 0.8280
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- - Recall: 0.7951
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- - F1: 0.7944
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- - Binary: 0.8569
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  ## Model description
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@@ -59,58 +59,58 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Binary |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
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- | No log | 0.19 | 50 | 4.3438 | 0.0566 | 0.0357 | 0.0566 | 0.0270 | 0.3183 |
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- | No log | 0.38 | 100 | 3.9861 | 0.0916 | 0.0269 | 0.0916 | 0.0306 | 0.3604 |
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- | No log | 0.58 | 150 | 3.7184 | 0.1429 | 0.0837 | 0.1429 | 0.0727 | 0.3954 |
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- | No log | 0.77 | 200 | 3.5059 | 0.2345 | 0.2019 | 0.2345 | 0.1717 | 0.4631 |
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- | No log | 0.96 | 250 | 3.3078 | 0.2857 | 0.2031 | 0.2857 | 0.2069 | 0.4989 |
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- | 3.9492 | 1.15 | 300 | 3.1185 | 0.3396 | 0.2410 | 0.3396 | 0.2564 | 0.5412 |
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- | 3.9492 | 1.34 | 350 | 2.9671 | 0.3666 | 0.3559 | 0.3666 | 0.3003 | 0.5582 |
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- | 3.9492 | 1.53 | 400 | 2.8265 | 0.4151 | 0.3929 | 0.4151 | 0.3473 | 0.5911 |
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- | 3.9492 | 1.73 | 450 | 2.6754 | 0.5040 | 0.4403 | 0.5040 | 0.4386 | 0.6523 |
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- | 3.9492 | 1.92 | 500 | 2.5560 | 0.5148 | 0.4664 | 0.5148 | 0.4591 | 0.6593 |
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- | 3.0798 | 2.11 | 550 | 2.4304 | 0.5660 | 0.5781 | 0.5660 | 0.5243 | 0.6968 |
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- | 3.0798 | 2.3 | 600 | 2.3227 | 0.5768 | 0.5487 | 0.5768 | 0.5238 | 0.7065 |
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- | 3.0798 | 2.49 | 650 | 2.2025 | 0.6011 | 0.5784 | 0.6011 | 0.5567 | 0.7240 |
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- | 3.0798 | 2.68 | 700 | 2.1138 | 0.6199 | 0.5967 | 0.6199 | 0.5743 | 0.7326 |
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- | 3.0798 | 2.88 | 750 | 2.0058 | 0.6307 | 0.6042 | 0.6307 | 0.5840 | 0.7420 |
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- | 2.5472 | 3.07 | 800 | 1.9306 | 0.6577 | 0.6453 | 0.6577 | 0.6202 | 0.7617 |
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- | 2.5472 | 3.26 | 850 | 1.8359 | 0.6604 | 0.6700 | 0.6604 | 0.6243 | 0.7644 |
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- | 2.5472 | 3.45 | 900 | 1.7841 | 0.6712 | 0.6500 | 0.6712 | 0.6277 | 0.7701 |
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- | 2.5472 | 3.64 | 950 | 1.7083 | 0.6765 | 0.6906 | 0.6765 | 0.6423 | 0.7739 |
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- | 2.5472 | 3.84 | 1000 | 1.6311 | 0.7089 | 0.7518 | 0.7089 | 0.6864 | 0.7976 |
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- | 2.1755 | 4.03 | 1050 | 1.5739 | 0.6765 | 0.6801 | 0.6765 | 0.6404 | 0.7747 |
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- | 2.1755 | 4.22 | 1100 | 1.5318 | 0.7008 | 0.7197 | 0.7008 | 0.6679 | 0.7919 |
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- | 2.1755 | 4.41 | 1150 | 1.4939 | 0.7143 | 0.7365 | 0.7143 | 0.6908 | 0.8003 |
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- | 2.1755 | 4.6 | 1200 | 1.4532 | 0.7278 | 0.7410 | 0.7278 | 0.7051 | 0.8108 |
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- | 2.1755 | 4.79 | 1250 | 1.3933 | 0.7305 | 0.7554 | 0.7305 | 0.7152 | 0.8127 |
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- | 2.1755 | 4.99 | 1300 | 1.3863 | 0.7143 | 0.7404 | 0.7143 | 0.6923 | 0.8013 |
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- | 1.9226 | 5.18 | 1350 | 1.3064 | 0.7493 | 0.7955 | 0.7493 | 0.7351 | 0.8248 |
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- | 1.9226 | 5.37 | 1400 | 1.2828 | 0.7520 | 0.7651 | 0.7520 | 0.7361 | 0.8288 |
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- | 1.9226 | 5.56 | 1450 | 1.2408 | 0.7520 | 0.7739 | 0.7520 | 0.7374 | 0.8267 |
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- | 1.9226 | 5.75 | 1500 | 1.2134 | 0.7628 | 0.7862 | 0.7628 | 0.7507 | 0.8342 |
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- | 1.9226 | 5.94 | 1550 | 1.1905 | 0.7628 | 0.7948 | 0.7628 | 0.7484 | 0.8353 |
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- | 1.7422 | 6.14 | 1600 | 1.1820 | 0.7547 | 0.7966 | 0.7547 | 0.7427 | 0.8286 |
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- | 1.7422 | 6.33 | 1650 | 1.1576 | 0.7574 | 0.8034 | 0.7574 | 0.7453 | 0.8305 |
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- | 1.7422 | 6.52 | 1700 | 1.1313 | 0.7574 | 0.7991 | 0.7574 | 0.7486 | 0.8315 |
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- | 1.7422 | 6.71 | 1750 | 1.1140 | 0.7709 | 0.8030 | 0.7709 | 0.7620 | 0.8410 |
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- | 1.7422 | 6.9 | 1800 | 1.0973 | 0.7628 | 0.7881 | 0.7628 | 0.7563 | 0.8353 |
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- | 1.6131 | 7.09 | 1850 | 1.0891 | 0.7709 | 0.8084 | 0.7709 | 0.7670 | 0.8412 |
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- | 1.6131 | 7.29 | 1900 | 1.0634 | 0.7601 | 0.7970 | 0.7601 | 0.7520 | 0.8345 |
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- | 1.6131 | 7.48 | 1950 | 1.0521 | 0.7736 | 0.7937 | 0.7736 | 0.7655 | 0.8439 |
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- | 1.6131 | 7.67 | 2000 | 1.0334 | 0.7817 | 0.8189 | 0.7817 | 0.7752 | 0.8474 |
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- | 1.6131 | 7.86 | 2050 | 1.0233 | 0.7844 | 0.8077 | 0.7844 | 0.7740 | 0.8504 |
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- | 1.5198 | 8.05 | 2100 | 1.0091 | 0.7817 | 0.8098 | 0.7817 | 0.7735 | 0.8474 |
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- | 1.5198 | 8.25 | 2150 | 1.0165 | 0.7709 | 0.8120 | 0.7709 | 0.7669 | 0.8399 |
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- | 1.5198 | 8.44 | 2200 | 0.9963 | 0.7790 | 0.8136 | 0.7790 | 0.7721 | 0.8456 |
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- | 1.5198 | 8.63 | 2250 | 0.9857 | 0.7763 | 0.8197 | 0.7763 | 0.7728 | 0.8437 |
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- | 1.5198 | 8.82 | 2300 | 0.9730 | 0.7898 | 0.8255 | 0.7898 | 0.7877 | 0.8531 |
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- | 1.4558 | 9.01 | 2350 | 0.9699 | 0.7978 | 0.8347 | 0.7978 | 0.7965 | 0.8588 |
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- | 1.4558 | 9.2 | 2400 | 0.9636 | 0.7925 | 0.8309 | 0.7925 | 0.7927 | 0.8550 |
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- | 1.4558 | 9.4 | 2450 | 0.9541 | 0.7898 | 0.8252 | 0.7898 | 0.7891 | 0.8531 |
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- | 1.4558 | 9.59 | 2500 | 0.9534 | 0.7925 | 0.8317 | 0.7925 | 0.7939 | 0.8550 |
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- | 1.4558 | 9.78 | 2550 | 0.9518 | 0.7951 | 0.8280 | 0.7951 | 0.7944 | 0.8569 |
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- | 1.4558 | 9.97 | 2600 | 0.9532 | 0.7951 | 0.8280 | 0.7951 | 0.7944 | 0.8569 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
22
  It achieves the following results on the evaluation set:
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+ - Loss: 1.0124
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+ - Accuracy: 0.7574
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+ - Precision: 0.7773
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+ - Recall: 0.7574
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+ - F1: 0.7429
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+ - Binary: 0.8286
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Binary |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
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+ | No log | 0.19 | 50 | 4.2519 | 0.0566 | 0.0051 | 0.0566 | 0.0089 | 0.3305 |
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+ | No log | 0.38 | 100 | 3.9645 | 0.0539 | 0.0068 | 0.0539 | 0.0107 | 0.3321 |
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+ | No log | 0.58 | 150 | 3.7338 | 0.1105 | 0.0576 | 0.1105 | 0.0536 | 0.3717 |
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+ | No log | 0.77 | 200 | 3.5648 | 0.1617 | 0.0751 | 0.1617 | 0.0846 | 0.4084 |
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+ | No log | 0.96 | 250 | 3.4031 | 0.2183 | 0.1101 | 0.2183 | 0.1268 | 0.4488 |
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+ | 3.9542 | 1.15 | 300 | 3.2478 | 0.2102 | 0.1080 | 0.2102 | 0.1281 | 0.4450 |
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+ | 3.9542 | 1.34 | 350 | 3.0971 | 0.2992 | 0.1963 | 0.2992 | 0.2044 | 0.5081 |
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+ | 3.9542 | 1.53 | 400 | 2.9647 | 0.2992 | 0.2154 | 0.2992 | 0.2194 | 0.5100 |
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+ | 3.9542 | 1.73 | 450 | 2.8175 | 0.3774 | 0.3235 | 0.3774 | 0.3129 | 0.5628 |
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+ | 3.9542 | 1.92 | 500 | 2.6989 | 0.4528 | 0.3689 | 0.4528 | 0.3734 | 0.6129 |
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+ | 3.1802 | 2.11 | 550 | 2.5825 | 0.4798 | 0.4392 | 0.4798 | 0.4132 | 0.6345 |
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+ | 3.1802 | 2.3 | 600 | 2.4777 | 0.4960 | 0.4381 | 0.4960 | 0.4257 | 0.6458 |
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+ | 3.1802 | 2.49 | 650 | 2.3896 | 0.5067 | 0.4835 | 0.5067 | 0.4514 | 0.6534 |
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+ | 3.1802 | 2.68 | 700 | 2.2850 | 0.5553 | 0.5319 | 0.5553 | 0.5060 | 0.6873 |
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+ | 3.1802 | 2.88 | 750 | 2.1647 | 0.5660 | 0.5312 | 0.5660 | 0.5136 | 0.6938 |
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+ | 2.6685 | 3.07 | 800 | 2.0787 | 0.5660 | 0.5682 | 0.5660 | 0.5299 | 0.6949 |
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+ | 2.6685 | 3.26 | 850 | 1.9976 | 0.5849 | 0.5871 | 0.5849 | 0.5490 | 0.7078 |
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+ | 2.6685 | 3.45 | 900 | 1.9318 | 0.6119 | 0.5932 | 0.6119 | 0.5737 | 0.7278 |
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+ | 2.6685 | 3.64 | 950 | 1.8600 | 0.6065 | 0.5880 | 0.6065 | 0.5629 | 0.7240 |
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+ | 2.6685 | 3.84 | 1000 | 1.7730 | 0.6496 | 0.6337 | 0.6496 | 0.6135 | 0.7550 |
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+ | 2.2863 | 4.03 | 1050 | 1.7003 | 0.6765 | 0.6607 | 0.6765 | 0.6427 | 0.7720 |
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+ | 2.2863 | 4.22 | 1100 | 1.6632 | 0.6658 | 0.6876 | 0.6658 | 0.6364 | 0.7655 |
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+ | 2.2863 | 4.41 | 1150 | 1.6066 | 0.6739 | 0.6552 | 0.6739 | 0.6371 | 0.7712 |
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+ | 2.2863 | 4.6 | 1200 | 1.5495 | 0.6900 | 0.6841 | 0.6900 | 0.6616 | 0.7825 |
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+ | 2.2863 | 4.79 | 1250 | 1.5232 | 0.6631 | 0.6333 | 0.6631 | 0.6295 | 0.7644 |
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+ | 2.2863 | 4.99 | 1300 | 1.4847 | 0.6900 | 0.6985 | 0.6900 | 0.6668 | 0.7825 |
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+ | 2.0189 | 5.18 | 1350 | 1.4253 | 0.6927 | 0.6710 | 0.6927 | 0.6586 | 0.7833 |
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+ | 2.0189 | 5.37 | 1400 | 1.4005 | 0.7008 | 0.6947 | 0.7008 | 0.6729 | 0.7900 |
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+ | 2.0189 | 5.56 | 1450 | 1.3482 | 0.7143 | 0.7217 | 0.7143 | 0.6926 | 0.7984 |
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+ | 2.0189 | 5.75 | 1500 | 1.3130 | 0.7089 | 0.7150 | 0.7089 | 0.6866 | 0.7957 |
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+ | 2.0189 | 5.94 | 1550 | 1.2733 | 0.7332 | 0.7519 | 0.7332 | 0.7117 | 0.8127 |
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+ | 1.8234 | 6.14 | 1600 | 1.2586 | 0.7278 | 0.7585 | 0.7278 | 0.7101 | 0.8089 |
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+ | 1.8234 | 6.33 | 1650 | 1.2376 | 0.7251 | 0.7509 | 0.7251 | 0.7067 | 0.8059 |
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+ | 1.8234 | 6.52 | 1700 | 1.2169 | 0.7251 | 0.7454 | 0.7251 | 0.7070 | 0.8059 |
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+ | 1.8234 | 6.71 | 1750 | 1.2007 | 0.7358 | 0.7476 | 0.7358 | 0.7162 | 0.8135 |
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+ | 1.8234 | 6.9 | 1800 | 1.1814 | 0.7278 | 0.7410 | 0.7278 | 0.7069 | 0.8078 |
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+ | 1.6833 | 7.09 | 1850 | 1.1559 | 0.7358 | 0.7627 | 0.7358 | 0.7184 | 0.8135 |
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+ | 1.6833 | 7.29 | 1900 | 1.1305 | 0.7574 | 0.7876 | 0.7574 | 0.7432 | 0.8286 |
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+ | 1.6833 | 7.48 | 1950 | 1.1150 | 0.7385 | 0.7671 | 0.7385 | 0.7259 | 0.8173 |
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+ | 1.6833 | 7.67 | 2000 | 1.1024 | 0.7412 | 0.7925 | 0.7412 | 0.7269 | 0.8173 |
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+ | 1.6833 | 7.86 | 2050 | 1.0954 | 0.7358 | 0.7272 | 0.7358 | 0.7111 | 0.8135 |
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+ | 1.5919 | 8.05 | 2100 | 1.0778 | 0.7547 | 0.7598 | 0.7547 | 0.7342 | 0.8267 |
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+ | 1.5919 | 8.25 | 2150 | 1.0713 | 0.7385 | 0.7462 | 0.7385 | 0.7192 | 0.8164 |
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+ | 1.5919 | 8.44 | 2200 | 1.0495 | 0.7574 | 0.7719 | 0.7574 | 0.7405 | 0.8286 |
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+ | 1.5919 | 8.63 | 2250 | 1.0371 | 0.7574 | 0.7677 | 0.7574 | 0.7400 | 0.8296 |
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+ | 1.5919 | 8.82 | 2300 | 1.0452 | 0.7655 | 0.7876 | 0.7655 | 0.7540 | 0.8353 |
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+ | 1.5254 | 9.01 | 2350 | 1.0313 | 0.7601 | 0.7781 | 0.7601 | 0.7450 | 0.8315 |
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+ | 1.5254 | 9.2 | 2400 | 1.0243 | 0.7628 | 0.7862 | 0.7628 | 0.7494 | 0.8334 |
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+ | 1.5254 | 9.4 | 2450 | 1.0192 | 0.7520 | 0.7697 | 0.7520 | 0.7348 | 0.8259 |
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+ | 1.5254 | 9.59 | 2500 | 1.0140 | 0.7628 | 0.7859 | 0.7628 | 0.7490 | 0.8323 |
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+ | 1.5254 | 9.78 | 2550 | 1.0121 | 0.7601 | 0.7774 | 0.7601 | 0.7453 | 0.8305 |
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+ | 1.5254 | 9.97 | 2600 | 1.0124 | 0.7574 | 0.7773 | 0.7574 | 0.7429 | 0.8286 |
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  ### Framework versions
runs/Jun21_11-51-34_LAPTOP-1GID9RGH/events.out.tfevents.1718945495.LAPTOP-1GID9RGH.7328.0 CHANGED
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