Commit
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Parent(s):
c7f240a
End of training
Browse files- README.md +58 -0
- config.json +40 -0
- preprocessor_config.json +22 -0
- pytorch_model.bin +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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model-index:
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- name: Rice-Image-Classification-Model
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results: []
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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-Classification-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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- eval_loss: 0.1592
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- eval_accuracy: 0.9816
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- eval_runtime: 34.3485
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- eval_samples_per_second: 9.491
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- eval_steps_per_second: 2.387
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- epoch: 186.0
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- step: 10788
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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: 2e-05
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- train_batch_size: 32
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- eval_batch_size: 4
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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: 200
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### Framework versions
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- Transformers 4.34.0
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- Pytorch 2.1.0
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- Datasets 2.14.5
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- Tokenizers 0.14.1
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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": 0,
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"1": 1,
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"2": 2,
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"3": 3,
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"4": 4,
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"5": 5
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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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"0": 0,
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"1": 1,
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"2": 2,
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"3": 3,
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"4": 4,
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"5": 5
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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": "4.34.0"
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}
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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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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:0be2e9e27c5c603f235e3885274af32aa00f4a570899ecf6ba49fb30ee898441
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size 343278698
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:041a34dce57c2a9f94b2dbf45575e8edba08f1f3a0350be914ff1b3c3b83a2cf
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size 4472
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