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---
license: other
base_model: nvidia/mit-b0
tags:
- generated_from_trainer
model-index:
- name: segformer-b0-PLbubble
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# segformer-b0-PLbubble
This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1220
- Mean Iou: 1.0
- Mean Accuracy: 1.0
- Overall Accuracy: 1.0
- Per Category Iou: [1.0, nan]
- Per Category Accuracy: [1.0, nan]
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 6e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Per Category Iou | Per Category Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------------:|:-------------------------:|
| 0.4349 | 0.1333 | 20 | 0.6675 | 0.4882 | 0.9764 | 0.9764 | [0.9763812450566833, 0.0] | [0.9763812450566833, nan] |
| 0.3447 | 0.2667 | 40 | 0.5703 | 0.4808 | 0.9615 | 0.9615 | [0.9615355039985939, 0.0] | [0.9615355039985939, nan] |
| 0.2628 | 0.4 | 60 | 0.4469 | 0.4972 | 0.9945 | 0.9945 | [0.9944809929475349, 0.0] | [0.9944809929475349, nan] |
| 0.2494 | 0.5333 | 80 | 0.3912 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.1228 | 0.6667 | 100 | 0.2821 | 0.4969 | 0.9938 | 0.9938 | [0.9937532268872484, 0.0] | [0.9937532268872484, nan] |
| 0.1172 | 0.8 | 120 | 0.1438 | 0.4976 | 0.9952 | 0.9952 | [0.9951531466956675, 0.0] | [0.9951531466956675, nan] |
| 0.1035 | 0.9333 | 140 | 0.1420 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0766 | 1.0667 | 160 | 0.2453 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0671 | 1.2 | 180 | 0.2341 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0321 | 1.3333 | 200 | 0.1829 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0274 | 1.4667 | 220 | 0.2913 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0351 | 1.6 | 240 | 0.1384 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.022 | 1.7333 | 260 | 0.1360 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0241 | 1.8667 | 280 | 0.0779 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0182 | 2.0 | 300 | 0.2171 | 0.4979 | 0.9958 | 0.9958 | [0.9957545835530363, 0.0] | [0.9957545835530363, nan] |
| 0.0204 | 2.1333 | 320 | 0.0848 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0137 | 2.2667 | 340 | 0.0955 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0143 | 2.4 | 360 | 0.1749 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0094 | 2.5333 | 380 | 0.2083 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0106 | 2.6667 | 400 | 0.0401 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.008 | 2.8 | 420 | 0.2128 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0074 | 2.9333 | 440 | 0.1823 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0076 | 3.0667 | 460 | 0.0463 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0102 | 3.2 | 480 | 0.0970 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0095 | 3.3333 | 500 | 0.0600 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0075 | 3.4667 | 520 | 0.1235 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0063 | 3.6 | 540 | 0.0755 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0058 | 3.7333 | 560 | 0.1467 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0071 | 3.8667 | 580 | 0.1714 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0057 | 4.0 | 600 | 0.1630 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0044 | 4.1333 | 620 | 0.1440 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0054 | 4.2667 | 640 | 0.1697 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0067 | 4.4 | 660 | 0.0370 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0056 | 4.5333 | 680 | 0.0017 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0047 | 4.6667 | 700 | 0.0768 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0037 | 4.8 | 720 | 0.1698 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0035 | 4.9333 | 740 | 0.1520 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0029 | 5.0667 | 760 | 0.1739 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0032 | 5.2 | 780 | 0.0686 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0036 | 5.3333 | 800 | 0.0714 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0046 | 5.4667 | 820 | 0.1578 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0031 | 5.6 | 840 | 0.0672 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0046 | 5.7333 | 860 | 0.1603 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0025 | 5.8667 | 880 | 0.0582 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0023 | 6.0 | 900 | 0.0454 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0028 | 6.1333 | 920 | 0.0213 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0022 | 6.2667 | 940 | 0.1520 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0022 | 6.4 | 960 | 0.1324 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0018 | 6.5333 | 980 | 0.1648 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0032 | 6.6667 | 1000 | 0.1482 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0027 | 6.8 | 1020 | 0.0168 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0025 | 6.9333 | 1040 | 0.1659 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0018 | 7.0667 | 1060 | 0.1450 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0033 | 7.2 | 1080 | 0.0364 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0015 | 7.3333 | 1100 | 0.0243 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0016 | 7.4667 | 1120 | 0.1476 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0016 | 7.6 | 1140 | 0.0828 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0015 | 7.7333 | 1160 | 0.1479 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0015 | 7.8667 | 1180 | 0.0738 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0019 | 8.0 | 1200 | 0.0908 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0028 | 8.1333 | 1220 | 0.1636 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.001 | 8.2667 | 1240 | 0.1233 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0014 | 8.4 | 1260 | 0.0878 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0021 | 8.5333 | 1280 | 0.0775 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0018 | 8.6667 | 1300 | 0.0159 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0012 | 8.8 | 1320 | 0.1521 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0016 | 8.9333 | 1340 | 0.1453 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0009 | 9.0667 | 1360 | 0.0766 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.001 | 9.2 | 1380 | 0.0553 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.001 | 9.3333 | 1400 | 0.1483 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0011 | 9.4667 | 1420 | 0.1172 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0021 | 9.6 | 1440 | 0.0503 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0009 | 9.7333 | 1460 | 0.2155 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0009 | 9.8667 | 1480 | 0.2272 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0008 | 10.0 | 1500 | 0.2017 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0019 | 10.1333 | 1520 | 0.1512 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0009 | 10.2667 | 1540 | 0.1371 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0008 | 10.4 | 1560 | 0.0169 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0015 | 10.5333 | 1580 | 0.1463 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0015 | 10.6667 | 1600 | 0.0502 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0015 | 10.8 | 1620 | 0.0403 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0012 | 10.9333 | 1640 | 0.0887 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0013 | 11.0667 | 1660 | 0.0072 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0007 | 11.2 | 1680 | 0.0104 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0011 | 11.3333 | 1700 | 0.1380 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0013 | 11.4667 | 1720 | 0.1270 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.001 | 11.6 | 1740 | 0.1037 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0008 | 11.7333 | 1760 | 0.0829 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0008 | 11.8667 | 1780 | 0.0124 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0011 | 12.0 | 1800 | 0.1691 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0007 | 12.1333 | 1820 | 0.0873 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0008 | 12.2667 | 1840 | 0.0830 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0011 | 12.4 | 1860 | 0.0893 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0007 | 12.5333 | 1880 | 0.0830 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0007 | 12.6667 | 1900 | 0.0718 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0008 | 12.8 | 1920 | 0.1217 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0005 | 12.9333 | 1940 | 0.0428 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0011 | 13.0667 | 1960 | 0.0398 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0014 | 13.2 | 1980 | 0.0986 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0006 | 13.3333 | 2000 | 0.0159 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0014 | 13.4667 | 2020 | 0.0748 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0005 | 13.6 | 2040 | 0.0898 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0008 | 13.7333 | 2060 | 0.0292 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0006 | 13.8667 | 2080 | 0.1166 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0008 | 14.0 | 2100 | 0.0387 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0009 | 14.1333 | 2120 | 0.1439 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0005 | 14.2667 | 2140 | 0.0181 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0005 | 14.4 | 2160 | 0.1052 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0011 | 14.5333 | 2180 | 0.0284 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0006 | 14.6667 | 2200 | 0.0839 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0008 | 14.8 | 2220 | 0.0989 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0006 | 14.9333 | 2240 | 0.0986 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0005 | 15.0667 | 2260 | 0.1199 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0008 | 15.2 | 2280 | 0.1042 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0019 | 15.3333 | 2300 | 0.0328 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.001 | 15.4667 | 2320 | 0.1013 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0006 | 15.6 | 2340 | 0.0943 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0008 | 15.7333 | 2360 | 0.0977 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0005 | 15.8667 | 2380 | 0.1455 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0004 | 16.0 | 2400 | 0.0704 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0004 | 16.1333 | 2420 | 0.0749 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0006 | 16.2667 | 2440 | 0.0422 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0005 | 16.4 | 2460 | 0.1148 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0005 | 16.5333 | 2480 | 0.1193 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0006 | 16.6667 | 2500 | 0.0921 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0004 | 16.8 | 2520 | 0.1161 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0004 | 16.9333 | 2540 | 0.0058 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 17.0667 | 2560 | 0.0716 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0004 | 17.2 | 2580 | 0.0665 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0008 | 17.3333 | 2600 | 0.0849 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0004 | 17.4667 | 2620 | 0.0328 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0004 | 17.6 | 2640 | 0.0908 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0007 | 17.7333 | 2660 | 0.0819 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0007 | 17.8667 | 2680 | 0.0499 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0006 | 18.0 | 2700 | 0.0174 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0005 | 18.1333 | 2720 | 0.1184 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 18.2667 | 2740 | 0.0366 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0004 | 18.4 | 2760 | 0.0037 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0004 | 18.5333 | 2780 | 0.0031 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0004 | 18.6667 | 2800 | 0.0479 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 18.8 | 2820 | 0.0271 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 18.9333 | 2840 | 0.0747 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0022 | 19.0667 | 2860 | 0.0904 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 19.2 | 2880 | 0.1316 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0004 | 19.3333 | 2900 | 0.1361 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0006 | 19.4667 | 2920 | 0.0948 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 19.6 | 2940 | 0.0495 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 19.7333 | 2960 | 0.0979 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0011 | 19.8667 | 2980 | 0.1175 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0005 | 20.0 | 3000 | 0.0074 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 20.1333 | 3020 | 0.1573 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0004 | 20.2667 | 3040 | 0.0160 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 20.4 | 3060 | 0.0915 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 20.5333 | 3080 | 0.0551 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 20.6667 | 3100 | 0.0192 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 20.8 | 3120 | 0.0277 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 20.9333 | 3140 | 0.1103 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 21.0667 | 3160 | 0.0565 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0006 | 21.2 | 3180 | 0.0097 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 21.3333 | 3200 | 0.0588 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 21.4667 | 3220 | 0.0182 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 21.6 | 3240 | 0.0832 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 21.7333 | 3260 | 0.0988 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0004 | 21.8667 | 3280 | 0.0841 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0004 | 22.0 | 3300 | 0.1069 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 22.1333 | 3320 | 0.1176 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0002 | 22.2667 | 3340 | 0.1257 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 22.4 | 3360 | 0.1052 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 22.5333 | 3380 | 0.0457 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 22.6667 | 3400 | 0.1074 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0007 | 22.8 | 3420 | 0.0232 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 22.9333 | 3440 | 0.0478 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0002 | 23.0667 | 3460 | 0.0762 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0002 | 23.2 | 3480 | 0.0857 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0002 | 23.3333 | 3500 | 0.1673 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0004 | 23.4667 | 3520 | 0.1409 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 23.6 | 3540 | 0.1192 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 23.7333 | 3560 | 0.1272 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 23.8667 | 3580 | 0.1327 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 24.0 | 3600 | 0.0691 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 24.1333 | 3620 | 0.1050 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 24.2667 | 3640 | 0.0339 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 24.4 | 3660 | 0.0274 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0002 | 24.5333 | 3680 | 0.1326 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 24.6667 | 3700 | 0.0904 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 24.8 | 3720 | 0.1312 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0002 | 24.9333 | 3740 | 0.0775 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0004 | 25.0667 | 3760 | 0.1099 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0002 | 25.2 | 3780 | 0.0509 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 25.3333 | 3800 | 0.1120 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0004 | 25.4667 | 3820 | 0.0131 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 25.6 | 3840 | 0.0640 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 25.7333 | 3860 | 0.0422 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0002 | 25.8667 | 3880 | 0.1482 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 26.0 | 3900 | 0.1136 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0002 | 26.1333 | 3920 | 0.1221 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0002 | 26.2667 | 3940 | 0.0991 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0004 | 26.4 | 3960 | 0.0169 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 26.5333 | 3980 | 0.1594 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0002 | 26.6667 | 4000 | 0.1176 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 26.8 | 4020 | 0.1065 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 26.9333 | 4040 | 0.0929 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0005 | 27.0667 | 4060 | 0.1079 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0002 | 27.2 | 4080 | 0.1030 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0002 | 27.3333 | 4100 | 0.0099 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0002 | 27.4667 | 4120 | 0.0439 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0005 | 27.6 | 4140 | 0.0538 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 27.7333 | 4160 | 0.1287 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0004 | 27.8667 | 4180 | 0.1273 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0002 | 28.0 | 4200 | 0.0277 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0002 | 28.1333 | 4220 | 0.0621 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0002 | 28.2667 | 4240 | 0.1391 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0002 | 28.4 | 4260 | 0.0709 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 28.5333 | 4280 | 0.1256 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0002 | 28.6667 | 4300 | 0.0285 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 28.8 | 4320 | 0.0218 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0002 | 28.9333 | 4340 | 0.0459 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 29.0667 | 4360 | 0.0612 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0004 | 29.2 | 4380 | 0.0804 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0004 | 29.3333 | 4400 | 0.0384 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 29.4667 | 4420 | 0.1265 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0004 | 29.6 | 4440 | 0.0007 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0002 | 29.7333 | 4460 | 0.0273 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0002 | 29.8667 | 4480 | 0.0411 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
| 0.0003 | 30.0 | 4500 | 0.1220 | 1.0 | 1.0 | 1.0 | [1.0, nan] | [1.0, nan] |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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