File size: 4,641 Bytes
c729401 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 | ---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: plug-classif-model
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. -->
# plug-classif-model
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5418
- Accuracy: 1.0
## 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- 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: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.695 | 0.1538 | 1 | 0.7619 | 0.1429 |
| 0.6096 | 0.3077 | 2 | 0.7630 | 0.2857 |
| 0.7567 | 0.4615 | 3 | 0.7897 | 0.2857 |
| 0.6185 | 0.6154 | 4 | 0.7943 | 0.2857 |
| 0.5869 | 0.7692 | 5 | 0.7740 | 0.2857 |
| 0.8098 | 0.9231 | 6 | 0.7680 | 0.4286 |
| 0.402 | 1.0 | 7 | 0.7535 | 0.2857 |
| 0.5498 | 1.1538 | 8 | 0.7027 | 0.2857 |
| 0.5556 | 1.3077 | 9 | 0.7100 | 0.2857 |
| 0.4257 | 1.4615 | 10 | 0.6922 | 0.4286 |
| 0.5488 | 1.6154 | 11 | 0.6592 | 0.4286 |
| 0.4829 | 1.7692 | 12 | 0.7471 | 0.2857 |
| 0.677 | 1.9231 | 13 | 0.6789 | 0.4286 |
| 0.3105 | 2.0 | 14 | 0.6908 | 0.4286 |
| 0.461 | 2.1538 | 15 | 0.6732 | 0.4286 |
| 0.388 | 2.3077 | 16 | 0.6960 | 0.5714 |
| 0.4678 | 2.4615 | 17 | 0.6274 | 0.5714 |
| 0.4753 | 2.6154 | 18 | 0.6437 | 0.5714 |
| 0.5482 | 2.7692 | 19 | 0.6570 | 0.5714 |
| 0.4301 | 2.9231 | 20 | 0.6745 | 0.7143 |
| 0.177 | 3.0 | 21 | 0.6477 | 0.4286 |
| 0.4159 | 3.1538 | 22 | 0.6018 | 0.5714 |
| 0.3089 | 3.3077 | 23 | 0.5951 | 0.5714 |
| 0.4568 | 3.4615 | 24 | 0.5659 | 0.8571 |
| 0.4791 | 3.6154 | 25 | 0.5845 | 0.8571 |
| 0.4097 | 3.7692 | 26 | 0.6343 | 0.8571 |
| 0.4327 | 3.9231 | 27 | 0.5930 | 0.8571 |
| 0.1493 | 4.0 | 28 | 0.5458 | 1.0 |
| 0.3021 | 4.1538 | 29 | 0.5421 | 1.0 |
| 0.3166 | 4.3077 | 30 | 0.5646 | 1.0 |
| 0.2537 | 4.4615 | 31 | 0.5960 | 0.8571 |
| 0.2853 | 4.6154 | 32 | 0.5636 | 0.8571 |
| 0.3353 | 4.7692 | 33 | 0.5513 | 1.0 |
| 0.3462 | 4.9231 | 34 | 0.5735 | 0.8571 |
| 0.1871 | 5.0 | 35 | 0.5109 | 1.0 |
| 0.2953 | 5.1538 | 36 | 0.5797 | 1.0 |
| 0.2655 | 5.3077 | 37 | 0.5374 | 1.0 |
| 0.352 | 5.4615 | 38 | 0.5245 | 1.0 |
| 0.3536 | 5.6154 | 39 | 0.5387 | 0.8571 |
| 0.2579 | 5.7692 | 40 | 0.5067 | 1.0 |
| 0.3356 | 5.9231 | 41 | 0.5992 | 0.8571 |
| 0.1094 | 6.0 | 42 | 0.5778 | 0.8571 |
| 0.3345 | 6.1538 | 43 | 0.4571 | 1.0 |
| 0.2314 | 6.3077 | 44 | 0.4651 | 1.0 |
| 0.3312 | 6.4615 | 45 | 0.4798 | 1.0 |
| 0.206 | 6.6154 | 46 | 0.4911 | 1.0 |
| 0.3101 | 6.7692 | 47 | 0.4788 | 1.0 |
| 0.3 | 6.9231 | 48 | 0.5418 | 1.0 |
### Framework versions
- Transformers 4.48.3
- Pytorch 2.6.0+cpu
- Datasets 3.2.0
- Tokenizers 0.21.0
|