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---
library_name: transformers
base_model: ellabettison/logo-matching-base
tags:
- generated_from_trainer
model-index:
- name: logo-matching-base
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. -->
# logo-matching-base
This model is a fine-tuned version of [ellabettison/logo-matching-base](https://huggingface.co./ellabettison/logo-matching-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Adjusted Rand Score: 0.1048
- Adjusted Mutual Info Score: 0.1103
- Homogeneity Score: 0.1072
- Completeness Score: 0.6399
- Fowlkes Mallows Score: 0.4934
- Pair Confusion Matrix: [[13442, 34208], [1176, 12430]]
- Loss: 0.1048
## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Adjusted Rand Score | Adjusted Mutual Info Score | Homogeneity Score | Completeness Score | Fowlkes Mallows Score | Pair Confusion Matrix | Validation Loss |
|:-------------:|:-----:|:----:|:-------------------:|:--------------------------:|:-----------------:|:------------------:|:---------------------:|:-------------------------------:|:---------------:|
| 0.0988 | 1.0 | 34 | 0.0667 | 0.1257 | 0.1492 | 0.5530 | 0.4345 | [[17354, 30296], [3408, 10198]] | 0.0667 |
| 0.0918 | 2.0 | 68 | 0.0512 | 0.0801 | 0.1155 | 0.4762 | 0.4303 | [[15840, 31810], [3306, 10300]] | 0.0512 |
| 0.0972 | 3.0 | 102 | 0.0494 | 0.1485 | 0.2067 | 0.4977 | 0.3496 | [[27372, 20278], [6908, 6698]] | 0.0494 |
| 0.1027 | 4.0 | 136 | 0.1550 | 0.1639 | 0.2052 | 0.5160 | 0.4118 | [[30918, 16732], [6132, 7474]] | 0.1550 |
| 0.0944 | 5.0 | 170 | 0.1798 | 0.1948 | 0.2833 | 0.5017 | 0.3910 | [[35784, 11866], [7490, 6116]] | 0.1798 |
| 0.09 | 6.0 | 204 | 0.1186 | 0.1355 | 0.1836 | 0.5103 | 0.4414 | [[23042, 24608], [4096, 9510]] | 0.1186 |
| 0.0858 | 7.0 | 238 | 0.0756 | 0.1533 | 0.2163 | 0.4937 | 0.3570 | [[29292, 18358], [7030, 6576]] | 0.0756 |
| 0.0735 | 8.0 | 272 | 0.1107 | 0.1555 | 0.2280 | 0.4815 | 0.3651 | [[31962, 15688], [7288, 6318]] | 0.1107 |
| 0.0868 | 9.0 | 306 | 0.2523 | 0.2273 | 0.3022 | 0.5371 | 0.4428 | [[36956, 10694], [6766, 6840]] | 0.2523 |
| 0.0932 | 10.0 | 340 | 0.2318 | 0.2251 | 0.3703 | 0.4901 | 0.3838 | [[41708, 5942], [9010, 4596]] | 0.2318 |
| 0.0642 | 11.0 | 374 | 0.1840 | 0.1915 | 0.2284 | 0.5528 | 0.4331 | [[31348, 16302], [5754, 7852]] | 0.1840 |
| 0.0918 | 12.0 | 408 | 0.1472 | 0.1783 | 0.2400 | 0.5135 | 0.3946 | [[32168, 15482], [6722, 6884]] | 0.1472 |
| 0.0818 | 13.0 | 442 | 0.2861 | 0.2445 | 0.3090 | 0.5556 | 0.4658 | [[37650, 10000], [6500, 7106]] | 0.2861 |
| 0.0877 | 14.0 | 476 | 0.1159 | 0.1723 | 0.2474 | 0.4934 | 0.3621 | [[32834, 14816], [7496, 6110]] | 0.1159 |
| 0.0849 | 15.0 | 510 | 0.1053 | 0.1092 | 0.1086 | 0.6293 | 0.4935 | [[13498, 34152], [1182, 12424]] | 0.1053 |
| 0.0927 | 16.0 | 544 | 0.1119 | 0.1599 | 0.2309 | 0.4880 | 0.3674 | [[31812, 15838], [7216, 6390]] | 0.1119 |
| 0.0794 | 17.0 | 578 | 0.2050 | 0.2036 | 0.2405 | 0.5662 | 0.4462 | [[31942, 15708], [5590, 8016]] | 0.2050 |
| 0.0888 | 18.0 | 612 | 0.2215 | 0.2213 | 0.3139 | 0.5143 | 0.4002 | [[38766, 8884], [7984, 5622]] | 0.2215 |
| 0.0815 | 19.0 | 646 | 0.1725 | 0.1935 | 0.2815 | 0.4997 | 0.3833 | [[35946, 11704], [7668, 5938]] | 0.1725 |
| 0.0796 | 20.0 | 680 | 0.1048 | 0.1103 | 0.1072 | 0.6399 | 0.4934 | [[13442, 34208], [1176, 12430]] | 0.1048 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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