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: 0.0416
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	0.73	2	0.0416	1.0
No log	1.73	4	0.0346	1.0
No log	2.73	6	0.0293	1.0
No log	3.73	8	0.0186	1.0
No log	4.73	10	0.0205	1.0
No log	5.73	12	0.0604	0.9730
No log	6.73	14	0.0332	1.0
No log	7.73	16	0.0250	1.0
No log	8.73	18	0.0386	1.0
0.2483	9.73	20	0.0438	1.0
0.2483	10.73	22	0.0447	1.0
0.2483	11.73	24	0.0676	0.9730
0.2483	12.73	26	0.0786	0.9730
0.2483	13.73	28	0.0389	1.0
0.2483	14.73	30	0.0278	1.0
0.2483	15.73	32	0.0250	1.0
0.2483	16.73	34	0.0283	1.0
0.2483	17.73	36	0.0502	0.9730
0.2483	18.73	38	0.0711	0.9730
0.1759	19.73	40	0.0637	0.9730
0.1759	20.73	42	0.0459	1.0
0.1759	21.73	44	0.0394	1.0
0.1759	22.73	46	0.0419	1.0
0.1759	23.73	48	0.0423	1.0
0.1759	24.73	50	0.0463	0.9730
0.1759	25.73	52	0.0503	0.9730
0.1759	26.73	54	0.0616	0.9730
0.1759	27.73	56	0.0641	0.9730
0.1759	28.73	58	0.0529	0.9730
0.1669	29.73	60	0.0485	0.9730
0.1669	30.73	62	0.0465	0.9730
0.1669	31.73	64	0.0456	0.9730
0.1669	32.73	66	0.0478	0.9730
0.1669	33.73	68	0.0467	0.9730
0.1669	34.73	70	0.0473	0.9730
0.1669	35.73	72	0.0486	0.9730
0.1669	36.73	74	0.0500	0.9730
0.1669	37.73	76	0.0502	0.9730
0.1669	38.73	78	0.0500	0.9730
0.1589	39.73	80	0.0493	0.9730

Framework versions

Transformers 4.21.3
Pytorch 1.12.1+cpu
Datasets 2.4.0
Tokenizers 0.12.1