End of training
Browse files- README.md +80 -0
- config.json +38 -0
- model.safetensors +3 -0
- preprocessor_config.json +22 -0
- runs/Apr02_15-30-38_3b08ee030899/events.out.tfevents.1712071855.3b08ee030899.528.0 +3 -0
- training_args.bin +3 -0
README.md
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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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model-index:
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- name: Rice-Image_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[:5000]
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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: 1.0
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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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# Rice-Image_model
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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: 0.0433
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- Accuracy: 1.0
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-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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- gradient_accumulation_steps: 4
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- total_train_batch_size: 64
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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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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.0756 | 0.99 | 62 | 0.0698 | 1.0 |
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| 0.0501 | 2.0 | 125 | 0.0482 | 1.0 |
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| 0.0435 | 2.98 | 186 | 0.0433 | 1.0 |
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### Framework versions
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- Transformers 4.38.2
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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config.json
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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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"id2label": {
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"0": "Arborio",
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"1": "Basmati",
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"2": "Ipsala",
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"3": "Jasmine",
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"4": "Karacadag"
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},
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"image_size": 224,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"Arborio": "0",
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"Basmati": "1",
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"Ipsala": "2",
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"Jasmine": "3",
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"Karacadag": "4"
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},
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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": "4.38.2"
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:c4131c4d8ac794b32aadd32175be18c4393278ec9ba3389f82e0f74936abb369
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size 343233204
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preprocessor_config.json
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{
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"do_normalize": true,
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"do_rescale": true,
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"do_resize": true,
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"image_mean": [
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0.5,
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0.5,
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0.5
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],
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"image_processor_type": "ViTImageProcessor",
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"image_std": [
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0.5,
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0.5,
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0.5
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],
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"resample": 2,
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"rescale_factor": 0.00392156862745098,
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"size": {
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"height": 224,
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"width": 224
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}
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}
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runs/Apr02_15-30-38_3b08ee030899/events.out.tfevents.1712071855.3b08ee030899.528.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:878ee762a59d6aed0f0f54c2189e5a63c34dcb306d1ee518c7ffd81ef3cbad08
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size 9748
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:18252d6fd3df3c9b4d26a578dd4e55ad8fac71627de35ae8f2e5ce36a8003d5a
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size 4920
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