File size: 2,284 Bytes
c07d4bb |
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 |
---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: car_orientation_classification_zoomed
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. -->
# car_orientation_classification_zoomed
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 None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6108
- Accuracy: 0.7597
## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 40
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9887 | 1.0 | 68 | 1.9011 | 0.3463 |
| 1.4388 | 2.0 | 136 | 1.3001 | 0.4594 |
| 1.1799 | 3.0 | 204 | 1.1267 | 0.4841 |
| 1.0245 | 4.0 | 272 | 0.9695 | 0.5936 |
| 0.8203 | 5.0 | 340 | 0.8157 | 0.6890 |
| 0.7146 | 6.0 | 408 | 0.7898 | 0.6678 |
| 0.6137 | 7.0 | 476 | 0.6343 | 0.7420 |
| 0.5746 | 8.0 | 544 | 0.6351 | 0.7527 |
| 0.5316 | 9.0 | 612 | 0.5899 | 0.7986 |
| 0.5073 | 10.0 | 680 | 0.6193 | 0.7491 |
| 0.4854 | 11.0 | 748 | 0.5721 | 0.7845 |
| 0.4347 | 12.0 | 816 | 0.6495 | 0.7562 |
| 0.3937 | 13.0 | 884 | 0.6108 | 0.7597 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
|