kensvin/sdss-cnn
Browse files- README.md +95 -1
- config.json +25 -0
- pytorch_model.bin +3 -0
- training_args.bin +3 -0
README.md
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---
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-
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---
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---
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: sdss-cnn
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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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# sdss-cnn
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This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1573
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- Accuracy: 0.9505
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0001
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- train_batch_size: 100
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- eval_batch_size: 100
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 40
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 1.0 | 80 | 0.4954 | 0.8635 |
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| No log | 2.0 | 160 | 0.2788 | 0.9055 |
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| No log | 3.0 | 240 | 0.2239 | 0.9085 |
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| No log | 4.0 | 320 | 0.1991 | 0.9325 |
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| No log | 5.0 | 400 | 0.1954 | 0.94 |
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| No log | 6.0 | 480 | 0.1854 | 0.9445 |
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| 0.3543 | 7.0 | 560 | 0.1891 | 0.9375 |
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| 0.3543 | 8.0 | 640 | 0.1777 | 0.943 |
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| 0.3543 | 9.0 | 720 | 0.1780 | 0.9415 |
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| 0.3543 | 10.0 | 800 | 0.1804 | 0.942 |
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| 0.3543 | 11.0 | 880 | 0.1734 | 0.9475 |
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| 0.3543 | 12.0 | 960 | 0.1689 | 0.947 |
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| 0.2022 | 13.0 | 1040 | 0.1698 | 0.9445 |
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| 0.2022 | 14.0 | 1120 | 0.1689 | 0.9405 |
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| 0.2022 | 15.0 | 1200 | 0.1650 | 0.9475 |
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| 0.2022 | 16.0 | 1280 | 0.1755 | 0.934 |
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| 0.2022 | 17.0 | 1360 | 0.1635 | 0.944 |
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| 0.2022 | 18.0 | 1440 | 0.1711 | 0.942 |
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| 0.1836 | 19.0 | 1520 | 0.1604 | 0.9485 |
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| 0.1836 | 20.0 | 1600 | 0.1595 | 0.95 |
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| 0.1836 | 21.0 | 1680 | 0.1613 | 0.9475 |
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| 0.1836 | 22.0 | 1760 | 0.1579 | 0.949 |
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| 0.1836 | 23.0 | 1840 | 0.1593 | 0.946 |
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| 0.1836 | 24.0 | 1920 | 0.1579 | 0.945 |
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| 0.167 | 25.0 | 2000 | 0.1584 | 0.9495 |
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| 0.167 | 26.0 | 2080 | 0.1573 | 0.9505 |
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| 0.167 | 27.0 | 2160 | 0.1596 | 0.945 |
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| 0.167 | 28.0 | 2240 | 0.1599 | 0.9435 |
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| 0.167 | 29.0 | 2320 | 0.1565 | 0.9485 |
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| 0.167 | 30.0 | 2400 | 0.1582 | 0.946 |
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| 0.167 | 31.0 | 2480 | 0.1563 | 0.95 |
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| 0.1568 | 32.0 | 2560 | 0.1563 | 0.95 |
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| 0.1568 | 33.0 | 2640 | 0.1573 | 0.9495 |
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| 0.1568 | 34.0 | 2720 | 0.1564 | 0.9465 |
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| 0.1568 | 35.0 | 2800 | 0.1557 | 0.95 |
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| 0.1568 | 36.0 | 2880 | 0.1554 | 0.949 |
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| 0.1568 | 37.0 | 2960 | 0.1562 | 0.948 |
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| 0.1515 | 38.0 | 3040 | 0.1555 | 0.948 |
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| 0.1515 | 39.0 | 3120 | 0.1557 | 0.95 |
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| 0.1515 | 40.0 | 3200 | 0.1559 | 0.9485 |
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### Framework versions
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- Transformers 4.33.3
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.5
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- Tokenizers 0.13.3
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config.json
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{
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"architectures": [
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"CNNModel"
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],
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"batch_size": 100,
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"dropout": [
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0.2,
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0.5
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],
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"filter_size": 3,
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"hidden_size": 128,
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"image_size": 128,
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"input_channels": 3,
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"model_type": "cnn",
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"num_classes": 3,
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"num_filters": [
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32,
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64
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],
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"padding": 0,
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"pool_size": 2,
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"stride": 1,
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"torch_dtype": "float32",
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"transformers_version": "4.33.3"
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:1a3a6d95e9f482a835672798e08383cc9a7480b15fe7084a292041ba0ad3d9f5
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size 29573515
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:917748bd9b3495555536d364ce7c2a54bf9ba941da54ce33b51c17da9ffb57b5
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size 4027
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