Hugging Face's logo

Akshay0706
/
Rice-Plant-50-Epochs-Model

Image Classification
Transformers
Safetensors
vit
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
Rice-Plant-50-Epochs-Model / README.md
Akshay0706's picture
Akshay0706
End of training
77f81a3
preview code
|
raw
history blame contribute delete
5.32 kB
metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
  - f1
model-index:
  - name: Rice-Plant-50-Epochs-Model
    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: 0.9688473520249221
          - name: F1
            type: f1
            value: 0.9686087085518211

Rice-Plant-50-Epochs-Model

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1649
  • Accuracy: 0.9688
  • F1: 0.9686

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: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 50

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
1.0399 1.0 115 0.6185 0.8910 0.8933
0.3392 2.0 230 0.2849 0.9502 0.9497
0.1633 3.0 345 0.2230 0.9439 0.9440
0.104 4.0 460 0.2022 0.9502 0.9495
0.0828 5.0 575 0.2081 0.9408 0.9406
0.0603 6.0 690 0.2301 0.9408 0.9403
0.0513 7.0 805 0.1704 0.9595 0.9593
0.042 8.0 920 0.1587 0.9626 0.9626
0.0356 9.0 1035 0.1606 0.9626 0.9625
0.0299 10.0 1150 0.1608 0.9657 0.9656
0.0262 11.0 1265 0.1553 0.9626 0.9625
0.0232 12.0 1380 0.1582 0.9657 0.9656
0.0207 13.0 1495 0.1588 0.9657 0.9656
0.0186 14.0 1610 0.1618 0.9657 0.9656
0.0168 15.0 1725 0.1618 0.9657 0.9656
0.0152 16.0 1840 0.1639 0.9657 0.9656
0.0139 17.0 1955 0.1649 0.9688 0.9686
0.0127 18.0 2070 0.1676 0.9657 0.9656
0.0117 19.0 2185 0.1688 0.9688 0.9686
0.0108 20.0 2300 0.1710 0.9626 0.9622
0.01 21.0 2415 0.1723 0.9657 0.9654
0.0093 22.0 2530 0.1739 0.9657 0.9654
0.0087 23.0 2645 0.1758 0.9626 0.9622
0.0081 24.0 2760 0.1776 0.9626 0.9622
0.0076 25.0 2875 0.1777 0.9657 0.9654
0.0071 26.0 2990 0.1792 0.9657 0.9654
0.0067 27.0 3105 0.1808 0.9657 0.9654
0.0063 28.0 3220 0.1822 0.9657 0.9654
0.006 29.0 3335 0.1834 0.9657 0.9654
0.0057 30.0 3450 0.1840 0.9657 0.9654
0.0054 31.0 3565 0.1855 0.9657 0.9654
0.0051 32.0 3680 0.1868 0.9657 0.9654
0.0049 33.0 3795 0.1877 0.9657 0.9654
0.0047 34.0 3910 0.1892 0.9657 0.9654
0.0045 35.0 4025 0.1900 0.9657 0.9654
0.0043 36.0 4140 0.1914 0.9657 0.9654
0.0042 37.0 4255 0.1919 0.9657 0.9654
0.004 38.0 4370 0.1929 0.9657 0.9654
0.0039 39.0 4485 0.1938 0.9657 0.9654
0.0037 40.0 4600 0.1953 0.9657 0.9654
0.0036 41.0 4715 0.1956 0.9657 0.9654
0.0035 42.0 4830 0.1965 0.9657 0.9654
0.0035 43.0 4945 0.1974 0.9657 0.9654
0.0034 44.0 5060 0.1981 0.9657 0.9654
0.0033 45.0 5175 0.1984 0.9657 0.9654
0.0032 46.0 5290 0.1986 0.9657 0.9654
0.0032 47.0 5405 0.1989 0.9657 0.9654
0.0032 48.0 5520 0.1993 0.9657 0.9654
0.0031 49.0 5635 0.1993 0.9657 0.9654
0.0031 50.0 5750 0.1993 0.9657 0.9654

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1