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Rice-Plant-50-Epochs-Model

Image Classification
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Safetensors
vit
Generated from Trainer
Eval Results
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  1. README.md +129 -0
  2. all_results.json +9 -0
  3. config.json +40 -0
  4. model.safetensors +3 -0
  5. preprocessor_config.json +22 -0
  6. train_results.json +9 -0
  7. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: google/vit-base-patch16-224-in21k
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - imagefolder
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+ metrics:
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+ - accuracy
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+ - f1
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+ model-index:
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+ - name: Rice-Plant-50-Epochs-Model
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+ results:
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+ - task:
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+ name: Image Classification
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+ type: image-classification
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+ dataset:
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+ name: imagefolder
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+ type: imagefolder
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+ config: default
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+ split: train
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9688473520249221
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+ - name: F1
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+ type: f1
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+ value: 0.9686087085518211
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # Rice-Plant-50-Epochs-Model
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+
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+ This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1649
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+ - Accuracy: 0.9688
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+ - F1: 0.9686
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 50
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 1.0399 | 1.0 | 115 | 0.6185 | 0.8910 | 0.8933 |
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+ | 0.3392 | 2.0 | 230 | 0.2849 | 0.9502 | 0.9497 |
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+ | 0.1633 | 3.0 | 345 | 0.2230 | 0.9439 | 0.9440 |
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+ | 0.104 | 4.0 | 460 | 0.2022 | 0.9502 | 0.9495 |
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+ | 0.0828 | 5.0 | 575 | 0.2081 | 0.9408 | 0.9406 |
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+ | 0.0603 | 6.0 | 690 | 0.2301 | 0.9408 | 0.9403 |
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+ | 0.0513 | 7.0 | 805 | 0.1704 | 0.9595 | 0.9593 |
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+ | 0.042 | 8.0 | 920 | 0.1587 | 0.9626 | 0.9626 |
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+ | 0.0356 | 9.0 | 1035 | 0.1606 | 0.9626 | 0.9625 |
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+ | 0.0299 | 10.0 | 1150 | 0.1608 | 0.9657 | 0.9656 |
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+ | 0.0262 | 11.0 | 1265 | 0.1553 | 0.9626 | 0.9625 |
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+ | 0.0232 | 12.0 | 1380 | 0.1582 | 0.9657 | 0.9656 |
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+ | 0.0207 | 13.0 | 1495 | 0.1588 | 0.9657 | 0.9656 |
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+ | 0.0186 | 14.0 | 1610 | 0.1618 | 0.9657 | 0.9656 |
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+ | 0.0168 | 15.0 | 1725 | 0.1618 | 0.9657 | 0.9656 |
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+ | 0.0152 | 16.0 | 1840 | 0.1639 | 0.9657 | 0.9656 |
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+ | 0.0139 | 17.0 | 1955 | 0.1649 | 0.9688 | 0.9686 |
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+ | 0.0127 | 18.0 | 2070 | 0.1676 | 0.9657 | 0.9656 |
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+ | 0.0117 | 19.0 | 2185 | 0.1688 | 0.9688 | 0.9686 |
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+ | 0.0108 | 20.0 | 2300 | 0.1710 | 0.9626 | 0.9622 |
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+ | 0.01 | 21.0 | 2415 | 0.1723 | 0.9657 | 0.9654 |
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+ | 0.0093 | 22.0 | 2530 | 0.1739 | 0.9657 | 0.9654 |
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+ | 0.0087 | 23.0 | 2645 | 0.1758 | 0.9626 | 0.9622 |
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+ | 0.0081 | 24.0 | 2760 | 0.1776 | 0.9626 | 0.9622 |
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+ | 0.0076 | 25.0 | 2875 | 0.1777 | 0.9657 | 0.9654 |
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+ | 0.0071 | 26.0 | 2990 | 0.1792 | 0.9657 | 0.9654 |
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+ | 0.0067 | 27.0 | 3105 | 0.1808 | 0.9657 | 0.9654 |
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+ | 0.0063 | 28.0 | 3220 | 0.1822 | 0.9657 | 0.9654 |
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+ | 0.006 | 29.0 | 3335 | 0.1834 | 0.9657 | 0.9654 |
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+ | 0.0057 | 30.0 | 3450 | 0.1840 | 0.9657 | 0.9654 |
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+ | 0.0054 | 31.0 | 3565 | 0.1855 | 0.9657 | 0.9654 |
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+ | 0.0051 | 32.0 | 3680 | 0.1868 | 0.9657 | 0.9654 |
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+ | 0.0049 | 33.0 | 3795 | 0.1877 | 0.9657 | 0.9654 |
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+ | 0.0047 | 34.0 | 3910 | 0.1892 | 0.9657 | 0.9654 |
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+ | 0.0045 | 35.0 | 4025 | 0.1900 | 0.9657 | 0.9654 |
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+ | 0.0043 | 36.0 | 4140 | 0.1914 | 0.9657 | 0.9654 |
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+ | 0.0042 | 37.0 | 4255 | 0.1919 | 0.9657 | 0.9654 |
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+ | 0.004 | 38.0 | 4370 | 0.1929 | 0.9657 | 0.9654 |
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+ | 0.0039 | 39.0 | 4485 | 0.1938 | 0.9657 | 0.9654 |
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+ | 0.0037 | 40.0 | 4600 | 0.1953 | 0.9657 | 0.9654 |
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+ | 0.0036 | 41.0 | 4715 | 0.1956 | 0.9657 | 0.9654 |
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+ | 0.0035 | 42.0 | 4830 | 0.1965 | 0.9657 | 0.9654 |
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+ | 0.0035 | 43.0 | 4945 | 0.1974 | 0.9657 | 0.9654 |
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+ | 0.0034 | 44.0 | 5060 | 0.1981 | 0.9657 | 0.9654 |
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+ | 0.0033 | 45.0 | 5175 | 0.1984 | 0.9657 | 0.9654 |
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+ | 0.0032 | 46.0 | 5290 | 0.1986 | 0.9657 | 0.9654 |
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+ | 0.0032 | 47.0 | 5405 | 0.1989 | 0.9657 | 0.9654 |
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+ | 0.0032 | 48.0 | 5520 | 0.1993 | 0.9657 | 0.9654 |
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+ | 0.0031 | 49.0 | 5635 | 0.1993 | 0.9657 | 0.9654 |
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+ | 0.0031 | 50.0 | 5750 | 0.1993 | 0.9657 | 0.9654 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
all_results.json ADDED
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+ {
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+ "epoch": 50.0,
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+ "total_flos": 7.083021773205504e+18,
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+ "train_loss": 0.04543054695233055,
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+ "train_runtime": 7193.0527,
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+ "train_samples": 1828,
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+ "train_samples_per_second": 12.707,
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+ "train_steps_per_second": 0.799
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+ }
config.json ADDED
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+ {
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+ "_name_or_path": "google/vit-base-patch16-224-in21k",
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+ "architectures": [
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+ "ViTForImageClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.0,
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+ "encoder_stride": 16,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.0,
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+ "hidden_size": 768,
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+ "image_size": 224,
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+ "initializer_range": 0.02,
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+ "3": 3,
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+ "5": 5
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+ "layer_norm_eps": 1e-12,
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+ "model_type": "vit",
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+ "num_attention_heads": 12,
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+ "num_channels": 3,
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+ "num_hidden_layers": 12,
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+ "patch_size": 16,
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+ "problem_type": "single_label_classification",
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+ "qkv_bias": true,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.35.0"
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+ }
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+ "image_mean": [
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+ "image_processor_type": "ViTImageProcessor",
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