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: 0.0188
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	0.1456	0.9574
No log	1.86	6	0.0900	0.9787
No log	2.86	9	0.0621	1.0
No log	3.86	12	0.0635	0.9787
No log	4.86	15	0.0535	0.9787
No log	5.86	18	0.0663	0.9574
0.3029	6.86	21	0.0492	0.9787
0.3029	7.86	24	0.0559	0.9787
0.3029	8.86	27	0.0664	0.9787
0.3029	9.86	30	0.0643	0.9787
0.3029	10.86	33	0.0558	0.9787
0.3029	11.86	36	0.0365	1.0
0.3029	12.86	39	0.0438	0.9787
0.2212	13.86	42	0.0456	0.9787
0.2212	14.86	45	0.0402	0.9787
0.2212	15.86	48	0.0351	0.9787
0.2212	16.86	51	0.0359	0.9787
0.2212	17.86	54	0.0427	0.9787
0.2212	18.86	57	0.0490	0.9574
0.186	19.86	60	0.0396	0.9787
0.186	20.86	63	0.0291	0.9787
0.186	21.86	66	0.0152	1.0
0.186	22.86	69	0.0142	1.0
0.186	23.86	72	0.0178	1.0
0.186	24.86	75	0.0176	1.0
0.186	25.86	78	0.0151	1.0
0.1751	26.86	81	0.0110	1.0
0.1751	27.86	84	0.0121	1.0
0.1751	28.86	87	0.0158	1.0
0.1751	29.86	90	0.0250	1.0
0.1751	30.86	93	0.0292	1.0
0.1751	31.86	96	0.0260	1.0
0.1751	32.86	99	0.0206	1.0
0.1614	33.86	102	0.0181	1.0
0.1614	34.86	105	0.0170	1.0
0.1614	35.86	108	0.0170	1.0
0.1614	36.86	111	0.0177	1.0
0.1614	37.86	114	0.0188	1.0
0.1614	38.86	117	0.0189	1.0
0.1483	39.86	120	0.0188	1.0

Framework versions

Transformers 4.23.1
Pytorch 1.12.1+cu113
Datasets 2.6.0
Tokenizers 0.13.1