Model save
Browse files- README.md +35 -66
- all_results.json +6 -11
- model.safetensors +1 -1
- runs/Apr17_15-48-28_43f826248acb/events.out.tfevents.1713373470.43f826248acb.34.1 +3 -0
- runs/Apr17_17-04-50_43f826248acb/events.out.tfevents.1713373508.43f826248acb.34.2 +3 -0
- train_results.json +6 -6
- trainer_state.json +2472 -258
- training_args.bin +1 -1
README.md
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.
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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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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.
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- Accuracy: 0.
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## Model description
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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:
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- eval_batch_size: 8
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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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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.1173 | 5.1 | 3200 | 1.0067 | 0.7610 |
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| 0.1313 | 5.25 | 3300 | 1.1971 | 0.7267 |
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| 0.2142 | 5.41 | 3400 | 1.1455 | 0.74 |
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| 0.1302 | 5.57 | 3500 | 1.0319 | 0.7629 |
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| 0.2193 | 5.73 | 3600 | 0.9746 | 0.7733 |
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| 0.1778 | 5.89 | 3700 | 1.0207 | 0.7552 |
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| 0.1003 | 6.05 | 3800 | 1.0538 | 0.7638 |
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| 0.1644 | 6.21 | 3900 | 1.1832 | 0.7305 |
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| 0.1843 | 6.37 | 4000 | 1.0814 | 0.7495 |
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| 0.129 | 6.53 | 4100 | 1.2479 | 0.72 |
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| 0.17 | 6.69 | 4200 | 1.1575 | 0.7419 |
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| 0.2184 | 6.85 | 4300 | 1.0946 | 0.7562 |
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| 0.1506 | 7.01 | 4400 | 1.0580 | 0.7714 |
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| 0.1099 | 7.17 | 4500 | 1.0479 | 0.7638 |
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| 0.1226 | 7.32 | 4600 | 1.1307 | 0.7495 |
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| 0.2122 | 7.48 | 4700 | 1.2838 | 0.7286 |
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| 0.1565 | 7.64 | 4800 | 1.2040 | 0.7390 |
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| 0.151 | 7.8 | 4900 | 1.2361 | 0.7429 |
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| 0.0934 | 7.96 | 5000 | 1.1985 | 0.7457 |
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| 0.1374 | 8.12 | 5100 | 1.1365 | 0.7495 |
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| 0.1799 | 8.28 | 5200 | 1.1371 | 0.7581 |
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| 0.1496 | 8.44 | 5300 | 1.1775 | 0.7429 |
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| 0.0804 | 8.6 | 5400 | 1.1278 | 0.7562 |
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| 0.12 | 8.76 | 5500 | 1.1210 | 0.7533 |
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| 0.099 | 8.92 | 5600 | 1.1295 | 0.7486 |
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| 0.1429 | 9.08 | 5700 | 1.2079 | 0.7390 |
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| 0.0959 | 9.24 | 5800 | 1.1451 | 0.7476 |
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| 0.0263 | 9.39 | 5900 | 1.1176 | 0.7514 |
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| 0.0936 | 9.55 | 6000 | 1.1179 | 0.7533 |
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| 0.1332 | 9.71 | 6100 | 1.1387 | 0.7486 |
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| 0.071 | 9.87 | 6200 | 1.1523 | 0.7467 |
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### Framework versions
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.7666666666666667
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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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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0234
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- Accuracy: 0.7667
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## Model description
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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: 32
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- eval_batch_size: 8
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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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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.4299 | 0.32 | 100 | 0.7981 | 0.7457 |
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| 0.3903 | 0.64 | 200 | 0.7173 | 0.7771 |
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| 0.4296 | 0.96 | 300 | 0.6869 | 0.7876 |
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| 0.3589 | 1.27 | 400 | 0.9108 | 0.7314 |
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| 0.3007 | 1.59 | 500 | 0.9720 | 0.7133 |
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| 0.2817 | 1.91 | 600 | 0.8504 | 0.7486 |
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| 0.2754 | 2.23 | 700 | 0.9009 | 0.7410 |
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| 0.2226 | 2.55 | 800 | 0.9020 | 0.7495 |
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| 0.285 | 2.87 | 900 | 1.0012 | 0.7295 |
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| 0.2307 | 3.18 | 1000 | 0.8204 | 0.7810 |
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| 0.2398 | 3.5 | 1100 | 0.8857 | 0.7695 |
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| 0.1948 | 3.82 | 1200 | 0.9110 | 0.7571 |
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| 0.1962 | 4.14 | 1300 | 0.9775 | 0.7533 |
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| 0.2159 | 4.46 | 1400 | 0.9719 | 0.7457 |
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| 0.1361 | 4.78 | 1500 | 0.9262 | 0.7571 |
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| 0.1898 | 5.1 | 1600 | 0.9130 | 0.7705 |
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| 0.1153 | 5.41 | 1700 | 1.0409 | 0.7438 |
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| 0.1489 | 5.73 | 1800 | 1.0176 | 0.7495 |
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| 0.1515 | 6.05 | 1900 | 1.0507 | 0.7486 |
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| 0.1126 | 6.37 | 2000 | 1.1423 | 0.7210 |
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| 0.1319 | 6.69 | 2100 | 1.1008 | 0.7467 |
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| 0.1424 | 7.01 | 2200 | 1.0798 | 0.7419 |
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| 0.0955 | 7.32 | 2300 | 1.0767 | 0.7505 |
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| 0.1077 | 7.64 | 2400 | 1.0920 | 0.7457 |
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| 0.1048 | 7.96 | 2500 | 1.0040 | 0.7733 |
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| 0.0965 | 8.28 | 2600 | 1.0384 | 0.7610 |
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| 0.0995 | 8.6 | 2700 | 1.0423 | 0.7648 |
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| 0.1213 | 8.92 | 2800 | 1.0544 | 0.7619 |
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| 0.0863 | 9.24 | 2900 | 1.0454 | 0.7629 |
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| 0.0926 | 9.55 | 3000 | 1.0380 | 0.7676 |
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| 0.0536 | 9.87 | 3100 | 1.0234 | 0.7667 |
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### Framework versions
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all_results.json
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model.safetensors
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train_results.json
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trainer_state.json
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