|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: delivery_truck_classification |
|
results: |
|
- task: |
|
name: Image Classification |
|
type: image-classification |
|
dataset: |
|
name: imagefolder |
|
type: imagefolder |
|
config: default |
|
split: train |
|
args: default |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 1.0 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# delivery_truck_classification |
|
|
|
This model is a fine-tuned version of [JEdward7777/delivery_truck_classification](https://huggingface.co/JEdward7777/delivery_truck_classification) on the imagefolder dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0261 |
|
- 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: 32 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 128 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| No log | 0.86 | 3 | 0.0261 | 1.0 | |
|
| No log | 1.86 | 6 | 0.0246 | 1.0 | |
|
| No log | 2.86 | 9 | 0.0350 | 0.9792 | |
|
| No log | 3.86 | 12 | 0.0298 | 1.0 | |
|
| No log | 4.86 | 15 | 0.0362 | 0.9792 | |
|
| No log | 5.86 | 18 | 0.0541 | 0.9792 | |
|
| 0.2214 | 6.86 | 21 | 0.0363 | 0.9792 | |
|
| 0.2214 | 7.86 | 24 | 0.0221 | 1.0 | |
|
| 0.2214 | 8.86 | 27 | 0.0366 | 0.9792 | |
|
| 0.2214 | 9.86 | 30 | 0.0502 | 0.9792 | |
|
| 0.2214 | 10.86 | 33 | 0.0355 | 0.9792 | |
|
| 0.2214 | 11.86 | 36 | 0.0218 | 1.0 | |
|
| 0.2214 | 12.86 | 39 | 0.0140 | 1.0 | |
|
| 0.183 | 13.86 | 42 | 0.0172 | 1.0 | |
|
| 0.183 | 14.86 | 45 | 0.0300 | 0.9792 | |
|
| 0.183 | 15.86 | 48 | 0.0589 | 0.9792 | |
|
| 0.183 | 16.86 | 51 | 0.0693 | 0.9792 | |
|
| 0.183 | 17.86 | 54 | 0.0496 | 0.9792 | |
|
| 0.183 | 18.86 | 57 | 0.0316 | 0.9792 | |
|
| 0.1706 | 19.86 | 60 | 0.0341 | 0.9792 | |
|
| 0.1706 | 20.86 | 63 | 0.0348 | 0.9792 | |
|
| 0.1706 | 21.86 | 66 | 0.0344 | 0.9792 | |
|
| 0.1706 | 22.86 | 69 | 0.0469 | 0.9792 | |
|
| 0.1706 | 23.86 | 72 | 0.0597 | 0.9792 | |
|
| 0.1706 | 24.86 | 75 | 0.0530 | 0.9792 | |
|
| 0.1706 | 25.86 | 78 | 0.0402 | 0.9792 | |
|
| 0.1644 | 26.86 | 81 | 0.0362 | 0.9792 | |
|
| 0.1644 | 27.86 | 84 | 0.0384 | 0.9792 | |
|
| 0.1644 | 28.86 | 87 | 0.0310 | 0.9792 | |
|
| 0.1644 | 29.86 | 90 | 0.0293 | 0.9792 | |
|
| 0.1644 | 30.86 | 93 | 0.0375 | 0.9792 | |
|
| 0.1644 | 31.86 | 96 | 0.0460 | 0.9792 | |
|
| 0.1644 | 32.86 | 99 | 0.0522 | 0.9792 | |
|
| 0.1539 | 33.86 | 102 | 0.0551 | 0.9792 | |
|
| 0.1539 | 34.86 | 105 | 0.0552 | 0.9792 | |
|
| 0.1539 | 35.86 | 108 | 0.0544 | 0.9792 | |
|
| 0.1539 | 36.86 | 111 | 0.0552 | 0.9792 | |
|
| 0.1539 | 37.86 | 114 | 0.0541 | 0.9792 | |
|
| 0.1539 | 38.86 | 117 | 0.0526 | 0.9792 | |
|
| 0.1401 | 39.86 | 120 | 0.0515 | 0.9792 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.23.1 |
|
- Pytorch 1.12.1+cu113 |
|
- Datasets 2.6.1 |
|
- Tokenizers 0.13.1 |
|
|
