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hubert-classifier-aug

Audio Classification
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hubert
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  1. README.md +61 -66
  2. runs/Jun23_19-27-29_LAPTOP-1GID9RGH/events.out.tfevents.1719145651.LAPTOP-1GID9RGH.21972.0 +2 -2
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: hubert-classifier
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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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- # hubert-classifier
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  This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.1058
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- - Accuracy: 0.7748
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- - Precision: 0.8018
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- - Recall: 0.7748
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- - F1: 0.7651
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- - Binary: 0.8455
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  ## Model description
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@@ -44,7 +44,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 3e-05
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  - train_batch_size: 32
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  - eval_batch_size: 32
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  - seed: 42
@@ -59,63 +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 | 0.17 | 50 | 4.2665 | 0.0412 | 0.0107 | 0.0412 | 0.0127 | 0.2923 |
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- | No log | 0.35 | 100 | 3.9427 | 0.0339 | 0.0016 | 0.0339 | 0.0030 | 0.3172 |
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- | No log | 0.52 | 150 | 3.7412 | 0.0363 | 0.0025 | 0.0363 | 0.0041 | 0.3206 |
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- | No log | 0.69 | 200 | 3.6193 | 0.0654 | 0.0238 | 0.0654 | 0.0259 | 0.3373 |
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- | No log | 0.86 | 250 | 3.4784 | 0.1041 | 0.0460 | 0.1041 | 0.0459 | 0.3663 |
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- | No log | 1.04 | 300 | 3.3705 | 0.1211 | 0.0602 | 0.1211 | 0.0466 | 0.3789 |
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- | No log | 1.21 | 350 | 3.2597 | 0.1768 | 0.0811 | 0.1768 | 0.0894 | 0.4218 |
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- | No log | 1.38 | 400 | 3.1606 | 0.2082 | 0.1867 | 0.2082 | 0.1416 | 0.4424 |
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- | No log | 1.55 | 450 | 3.0720 | 0.1913 | 0.1490 | 0.1913 | 0.1296 | 0.4312 |
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- | 3.6525 | 1.73 | 500 | 2.9557 | 0.2446 | 0.1432 | 0.2446 | 0.1609 | 0.4671 |
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- | 3.6525 | 1.9 | 550 | 2.8287 | 0.2857 | 0.2265 | 0.2857 | 0.2059 | 0.4973 |
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- | 3.6525 | 2.07 | 600 | 2.7005 | 0.3075 | 0.2103 | 0.3075 | 0.2154 | 0.5136 |
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- | 3.6525 | 2.24 | 650 | 2.6183 | 0.3414 | 0.2398 | 0.3414 | 0.2486 | 0.5341 |
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- | 3.6525 | 2.42 | 700 | 2.5133 | 0.3632 | 0.2942 | 0.3632 | 0.2732 | 0.5516 |
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- | 3.6525 | 2.59 | 750 | 2.4277 | 0.3753 | 0.3322 | 0.3753 | 0.2948 | 0.5615 |
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- | 3.6525 | 2.76 | 800 | 2.3329 | 0.4092 | 0.3538 | 0.4092 | 0.3338 | 0.5845 |
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- | 3.6525 | 2.93 | 850 | 2.2465 | 0.4407 | 0.4125 | 0.4407 | 0.3745 | 0.6073 |
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- | 3.6525 | 3.11 | 900 | 2.1792 | 0.4600 | 0.4329 | 0.4600 | 0.3995 | 0.6203 |
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- | 3.6525 | 3.28 | 950 | 2.1004 | 0.5109 | 0.4995 | 0.5109 | 0.4540 | 0.6550 |
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- | 2.6844 | 3.45 | 1000 | 2.0314 | 0.5109 | 0.4799 | 0.5109 | 0.4520 | 0.6557 |
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- | 2.6844 | 3.62 | 1050 | 1.9561 | 0.5400 | 0.5309 | 0.5400 | 0.4859 | 0.6743 |
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- | 2.6844 | 3.8 | 1100 | 1.9362 | 0.5472 | 0.5441 | 0.5472 | 0.5066 | 0.6804 |
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- | 2.6844 | 3.97 | 1150 | 1.8666 | 0.5642 | 0.5647 | 0.5642 | 0.5232 | 0.6930 |
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- | 2.6844 | 4.14 | 1200 | 1.8204 | 0.5811 | 0.5716 | 0.5811 | 0.5416 | 0.7048 |
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- | 2.6844 | 4.31 | 1250 | 1.7494 | 0.5908 | 0.6153 | 0.5908 | 0.5618 | 0.7109 |
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- | 2.6844 | 4.49 | 1300 | 1.6973 | 0.6126 | 0.6062 | 0.6126 | 0.5804 | 0.7291 |
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- | 2.6844 | 4.66 | 1350 | 1.6615 | 0.6053 | 0.5864 | 0.6053 | 0.5707 | 0.7211 |
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- | 2.6844 | 4.83 | 1400 | 1.6120 | 0.6295 | 0.6304 | 0.6295 | 0.6000 | 0.7385 |
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- | 2.6844 | 5.0 | 1450 | 1.5620 | 0.6610 | 0.6605 | 0.6610 | 0.6333 | 0.7615 |
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- | 2.1096 | 5.18 | 1500 | 1.5330 | 0.6538 | 0.6424 | 0.6538 | 0.6223 | 0.7581 |
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- | 2.1096 | 5.35 | 1550 | 1.5112 | 0.6707 | 0.6830 | 0.6707 | 0.6484 | 0.7707 |
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- | 2.1096 | 5.52 | 1600 | 1.4732 | 0.6659 | 0.6793 | 0.6659 | 0.6430 | 0.7685 |
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- | 2.1096 | 5.69 | 1650 | 1.4420 | 0.6755 | 0.6969 | 0.6755 | 0.6538 | 0.7734 |
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- | 2.1096 | 5.87 | 1700 | 1.4011 | 0.7094 | 0.7461 | 0.7094 | 0.6929 | 0.7988 |
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- | 2.1096 | 6.04 | 1750 | 1.3924 | 0.6780 | 0.6835 | 0.6780 | 0.6557 | 0.7760 |
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- | 2.1096 | 6.21 | 1800 | 1.3604 | 0.7022 | 0.7116 | 0.7022 | 0.6838 | 0.7937 |
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- | 2.1096 | 6.38 | 1850 | 1.3271 | 0.7070 | 0.7079 | 0.7070 | 0.6882 | 0.7954 |
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- | 2.1096 | 6.56 | 1900 | 1.3104 | 0.7264 | 0.7338 | 0.7264 | 0.7110 | 0.8099 |
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- | 2.1096 | 6.73 | 1950 | 1.2804 | 0.7312 | 0.7591 | 0.7312 | 0.7159 | 0.8131 |
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- | 1.7648 | 6.9 | 2000 | 1.2722 | 0.7312 | 0.7739 | 0.7312 | 0.7185 | 0.8131 |
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- | 1.7648 | 7.08 | 2050 | 1.2777 | 0.7240 | 0.7581 | 0.7240 | 0.7109 | 0.8099 |
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- | 1.7648 | 7.25 | 2100 | 1.2319 | 0.7288 | 0.7373 | 0.7288 | 0.7114 | 0.8123 |
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- | 1.7648 | 7.42 | 2150 | 1.2074 | 0.7433 | 0.7717 | 0.7433 | 0.7317 | 0.8215 |
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- | 1.7648 | 7.59 | 2200 | 1.2150 | 0.7433 | 0.7850 | 0.7433 | 0.7348 | 0.8235 |
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- | 1.7648 | 7.77 | 2250 | 1.1787 | 0.7603 | 0.7930 | 0.7603 | 0.7462 | 0.8344 |
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- | 1.7648 | 7.94 | 2300 | 1.1815 | 0.7676 | 0.7932 | 0.7676 | 0.7576 | 0.8404 |
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- | 1.7648 | 8.11 | 2350 | 1.1578 | 0.7676 | 0.7972 | 0.7676 | 0.7601 | 0.8404 |
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- | 1.7648 | 8.28 | 2400 | 1.1605 | 0.7651 | 0.7982 | 0.7651 | 0.7560 | 0.8387 |
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- | 1.7648 | 8.46 | 2450 | 1.1563 | 0.7627 | 0.7937 | 0.7627 | 0.7548 | 0.8370 |
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- | 1.5781 | 8.63 | 2500 | 1.1303 | 0.7579 | 0.7847 | 0.7579 | 0.7476 | 0.8337 |
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- | 1.5781 | 8.8 | 2550 | 1.1217 | 0.7797 | 0.8117 | 0.7797 | 0.7702 | 0.8489 |
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- | 1.5781 | 8.97 | 2600 | 1.1278 | 0.7724 | 0.8025 | 0.7724 | 0.7640 | 0.8438 |
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- | 1.5781 | 9.15 | 2650 | 1.1188 | 0.7748 | 0.8022 | 0.7748 | 0.7653 | 0.8455 |
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- | 1.5781 | 9.32 | 2700 | 1.1161 | 0.7676 | 0.7979 | 0.7676 | 0.7588 | 0.8404 |
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- | 1.5781 | 9.49 | 2750 | 1.1078 | 0.7748 | 0.8012 | 0.7748 | 0.7650 | 0.8446 |
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- | 1.5781 | 9.66 | 2800 | 1.1104 | 0.7724 | 0.7973 | 0.7724 | 0.7632 | 0.8429 |
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- | 1.5781 | 9.84 | 2850 | 1.1058 | 0.7748 | 0.8018 | 0.7748 | 0.7651 | 0.8455 |
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  ### Framework versions
 
9
  - recall
10
  - f1
11
  model-index:
12
+ - name: hubert-classifier-aug
13
  results: []
14
  ---
15
 
16
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
17
  should probably proofread and complete it, then remove this comment. -->
18
 
19
+ # hubert-classifier-aug
20
 
21
  This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on an unknown dataset.
22
  It achieves the following results on the evaluation set:
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+ - Loss: 3.0783
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+ - Accuracy: 0.2075
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+ - Precision: 0.1563
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+ - Recall: 0.2075
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+ - F1: 0.1504
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+ - Binary: 0.4396
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  ## Model description
31
 
 
44
  ### Training hyperparameters
45
 
46
  The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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  - train_batch_size: 32
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  - eval_batch_size: 32
50
  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Binary |
61
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
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+ | No log | 0.19 | 50 | 4.4148 | 0.0243 | 0.0244 | 0.0243 | 0.0114 | 0.1755 |
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+ | No log | 0.38 | 100 | 4.3445 | 0.0404 | 0.0101 | 0.0404 | 0.0123 | 0.2865 |
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+ | No log | 0.58 | 150 | 4.2100 | 0.0350 | 0.0154 | 0.0350 | 0.0080 | 0.3043 |
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+ | No log | 0.77 | 200 | 4.1002 | 0.0350 | 0.0185 | 0.0350 | 0.0088 | 0.3140 |
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+ | No log | 0.96 | 250 | 4.0141 | 0.0512 | 0.0295 | 0.0512 | 0.0232 | 0.3253 |
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+ | No log | 1.15 | 300 | 3.9438 | 0.0593 | 0.0321 | 0.0593 | 0.0293 | 0.3318 |
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+ | No log | 1.34 | 350 | 3.8728 | 0.0647 | 0.0290 | 0.0647 | 0.0281 | 0.3372 |
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+ | No log | 1.53 | 400 | 3.8297 | 0.0755 | 0.0242 | 0.0755 | 0.0331 | 0.3423 |
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+ | No log | 1.73 | 450 | 3.7627 | 0.0620 | 0.0186 | 0.0620 | 0.0263 | 0.3385 |
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+ | 4.147 | 1.92 | 500 | 3.7166 | 0.0728 | 0.0364 | 0.0728 | 0.0360 | 0.3437 |
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+ | 4.147 | 2.11 | 550 | 3.6779 | 0.0889 | 0.0425 | 0.0889 | 0.0486 | 0.3558 |
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+ | 4.147 | 2.3 | 600 | 3.6396 | 0.0755 | 0.0345 | 0.0755 | 0.0407 | 0.3447 |
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+ | 4.147 | 2.49 | 650 | 3.6005 | 0.0889 | 0.0336 | 0.0889 | 0.0412 | 0.3550 |
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+ | 4.147 | 2.68 | 700 | 3.5602 | 0.0970 | 0.0314 | 0.0970 | 0.0420 | 0.3631 |
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+ | 4.147 | 2.88 | 750 | 3.5309 | 0.0997 | 0.0473 | 0.0997 | 0.0507 | 0.3642 |
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+ | 4.147 | 3.07 | 800 | 3.5331 | 0.1051 | 0.0385 | 0.1051 | 0.0490 | 0.3615 |
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+ | 4.147 | 3.26 | 850 | 3.4774 | 0.1105 | 0.0507 | 0.1105 | 0.0604 | 0.3701 |
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+ | 4.147 | 3.45 | 900 | 3.4571 | 0.1159 | 0.0568 | 0.1159 | 0.0611 | 0.3730 |
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+ | 4.147 | 3.64 | 950 | 3.4265 | 0.1132 | 0.0431 | 0.1132 | 0.0582 | 0.3736 |
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+ | 3.6862 | 3.84 | 1000 | 3.4260 | 0.0970 | 0.0406 | 0.0970 | 0.0502 | 0.3582 |
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+ | 3.6862 | 4.03 | 1050 | 3.3821 | 0.1105 | 0.0421 | 0.1105 | 0.0542 | 0.3709 |
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+ | 3.6862 | 4.22 | 1100 | 3.3825 | 0.1186 | 0.0448 | 0.1186 | 0.0578 | 0.3725 |
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+ | 3.6862 | 4.41 | 1150 | 3.3575 | 0.1213 | 0.0507 | 0.1213 | 0.0634 | 0.3776 |
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+ | 3.6862 | 4.6 | 1200 | 3.3453 | 0.1267 | 0.0659 | 0.1267 | 0.0653 | 0.3790 |
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+ | 3.6862 | 4.79 | 1250 | 3.3205 | 0.1321 | 0.0592 | 0.1321 | 0.0736 | 0.3871 |
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+ | 3.6862 | 4.99 | 1300 | 3.2912 | 0.1294 | 0.0552 | 0.1294 | 0.0724 | 0.3868 |
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+ | 3.6862 | 5.18 | 1350 | 3.2741 | 0.1536 | 0.0731 | 0.1536 | 0.0880 | 0.4022 |
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+ | 3.6862 | 5.37 | 1400 | 3.2767 | 0.1509 | 0.0723 | 0.1509 | 0.0893 | 0.3978 |
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+ | 3.6862 | 5.56 | 1450 | 3.2485 | 0.1509 | 0.0743 | 0.1509 | 0.0907 | 0.4003 |
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+ | 3.4619 | 5.75 | 1500 | 3.2421 | 0.1509 | 0.0783 | 0.1509 | 0.0855 | 0.4003 |
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+ | 3.4619 | 5.94 | 1550 | 3.2366 | 0.1375 | 0.0686 | 0.1375 | 0.0754 | 0.3892 |
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+ | 3.4619 | 6.14 | 1600 | 3.2102 | 0.1456 | 0.0959 | 0.1456 | 0.0862 | 0.3965 |
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+ | 3.4619 | 6.33 | 1650 | 3.1962 | 0.1456 | 0.0688 | 0.1456 | 0.0858 | 0.3957 |
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+ | 3.4619 | 6.52 | 1700 | 3.1917 | 0.1590 | 0.1160 | 0.1590 | 0.0994 | 0.4035 |
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+ | 3.4619 | 6.71 | 1750 | 3.1746 | 0.1590 | 0.0922 | 0.1590 | 0.0978 | 0.4051 |
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+ | 3.4619 | 6.9 | 1800 | 3.1791 | 0.1590 | 0.0671 | 0.1590 | 0.0863 | 0.4059 |
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+ | 3.4619 | 7.09 | 1850 | 3.1714 | 0.1725 | 0.0952 | 0.1725 | 0.1028 | 0.4135 |
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+ | 3.4619 | 7.29 | 1900 | 3.1427 | 0.1725 | 0.1084 | 0.1725 | 0.1090 | 0.4194 |
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+ | 3.4619 | 7.48 | 1950 | 3.1410 | 0.1833 | 0.1313 | 0.1833 | 0.1221 | 0.4226 |
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+ | 3.3361 | 7.67 | 2000 | 3.1334 | 0.1806 | 0.1385 | 0.1806 | 0.1239 | 0.4197 |
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+ | 3.3361 | 7.86 | 2050 | 3.1246 | 0.1806 | 0.1474 | 0.1806 | 0.1193 | 0.4208 |
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+ | 3.3361 | 8.05 | 2100 | 3.1151 | 0.1995 | 0.1582 | 0.1995 | 0.1388 | 0.4332 |
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+ | 3.3361 | 8.25 | 2150 | 3.1085 | 0.2049 | 0.1578 | 0.2049 | 0.1439 | 0.4377 |
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+ | 3.3361 | 8.44 | 2200 | 3.0897 | 0.2102 | 0.1546 | 0.2102 | 0.1483 | 0.4445 |
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+ | 3.3361 | 8.63 | 2250 | 3.0934 | 0.2210 | 0.1511 | 0.2210 | 0.1541 | 0.4469 |
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+ | 3.3361 | 8.82 | 2300 | 3.0906 | 0.2102 | 0.1625 | 0.2102 | 0.1535 | 0.4394 |
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+ | 3.3361 | 9.01 | 2350 | 3.0792 | 0.2129 | 0.1586 | 0.2129 | 0.1573 | 0.4437 |
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+ | 3.3361 | 9.2 | 2400 | 3.0849 | 0.2049 | 0.1442 | 0.2049 | 0.1446 | 0.4358 |
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+ | 3.3361 | 9.4 | 2450 | 3.0794 | 0.2102 | 0.1576 | 0.2102 | 0.1532 | 0.4396 |
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+ | 3.2647 | 9.59 | 2500 | 3.0801 | 0.2129 | 0.1560 | 0.2129 | 0.1552 | 0.4415 |
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+ | 3.2647 | 9.78 | 2550 | 3.0823 | 0.2075 | 0.1669 | 0.2075 | 0.1521 | 0.4396 |
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+ | 3.2647 | 9.97 | 2600 | 3.0783 | 0.2075 | 0.1563 | 0.2075 | 0.1504 | 0.4396 |
 
 
 
 
 
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  ### Framework versions
runs/Jun23_19-27-29_LAPTOP-1GID9RGH/events.out.tfevents.1719145651.LAPTOP-1GID9RGH.21972.0 CHANGED
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