metadata

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

delivery_truck_classification

This model is a fine-tuned version of 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