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: 0.0431
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	1.0	3	0.1626	0.95
No log	2.0	6	0.1593	0.95
No log	3.0	9	0.1342	0.95
No log	4.0	12	0.0871	0.975
No log	5.0	15	0.0612	0.975
No log	6.0	18	0.0431	1.0
0.2745	7.0	21	0.0333	1.0
0.2745	8.0	24	0.0487	1.0
0.2745	9.0	27	0.0456	1.0
0.2745	10.0	30	0.0273	1.0
0.2745	11.0	33	0.0180	1.0
0.2745	12.0	36	0.0168	1.0
0.2745	13.0	39	0.0310	1.0
0.1782	14.0	42	0.0438	0.975
0.1782	15.0	45	0.0750	0.975
0.1782	16.0	48	0.0396	0.975
0.1782	17.0	51	0.0177	1.0
0.1782	18.0	54	0.0217	1.0
0.1782	19.0	57	0.0116	1.0
0.1624	20.0	60	0.0081	1.0
0.1624	21.0	63	0.0066	1.0
0.1624	22.0	66	0.0083	1.0
0.1624	23.0	69	0.0126	1.0
0.1624	24.0	72	0.0158	1.0
0.1624	25.0	75	0.0188	1.0
0.1624	26.0	78	0.0149	1.0
0.1475	27.0	81	0.0101	1.0
0.1475	28.0	84	0.0064	1.0
0.1475	29.0	87	0.0050	1.0
0.1475	30.0	90	0.0052	1.0
0.1475	31.0	93	0.0064	1.0
0.1475	32.0	96	0.0070	1.0
0.1475	33.0	99	0.0069	1.0
0.1345	34.0	102	0.0059	1.0
0.1345	35.0	105	0.0049	1.0
0.1345	36.0	108	0.0043	1.0
0.1345	37.0	111	0.0040	1.0
0.1345	38.0	114	0.0038	1.0
0.1345	39.0	117	0.0038	1.0
0.1232	40.0	120	0.0038	1.0

Framework versions

Transformers 4.21.3
Pytorch 1.12.1+cpu
Datasets 2.4.0
Tokenizers 0.12.1